BACK TO INDEX BACK TO OTHMAR FREY'S HOMEPAGE Publications of year 2018 Books and proceedings
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| Abstract: | Cost pressure forces infrastructure managers to work sustainably and efficiently. There-fore, track engineers face increasing difficulty to carry out necessary measures owing to budget restrictions. Consequently, they should be supported in prioritising. This requires an objective tool enabling proper condition monitoring as well as component-specific, preventive maintenance and renewal planning. Hence, the right measures are to be executed at the right time. This dissertation deals with a description of the railway track condition. A bottom-up approach provides an in-depth assessment of track using a variety of measurement signals and an aggregated component-specific assessment. Since the approach is based on well positioned measurement signals, it is valid for monitoring specific track sections as well as whole networks. Innovative analyses of various measurement signals form a sound basis to grasp their characteristics enabling a component specific condition evaluation of railway track. The use of historical measurement data allows for an analysis of track behaviour over time. A thorough validation process, including on-site inspections and excavations, shows that the presented approach is able to evaluate the actual condition of railway track. The assessment of the specific components condition can be used for timely maintenance as well as renewal planning. Based on correlation analyses, the component specific evaluations are aggregated into one holistic quality figure. This enables asset managers to monitor the asset condition network-wide as well as to predict future budget demands. |
@Book{landgraf2018SmartDataForSustainableRailwayAssetManagement,
author = {Matthias Landgraf},
publisher = {Verlag der Technischen Universit{\"a}t Graz},
title = {Smart data for sustainable Railway Asset Management: railway track: assessment - aggregation - asset management},
year = {2018},
isbn = {978-3-85125-569-0},
month = sep,
note = {basiert auf der Dissertation: Zustandsbeschreibung des Fahrwegs der Eisenbahn - von der Messdatenanalyse zum Anlagenmanagement, TU Graz, 2016},
series = {Monographic Series TU Graz : Railway Research},
abstract = {Cost pressure forces infrastructure managers to work sustainably and efficiently. There-fore, track engineers face increasing difficulty to carry out necessary measures owing to budget restrictions. Consequently, they should be supported in prioritising. This requires an objective tool enabling proper condition monitoring as well as component-specific, preventive maintenance and renewal planning. Hence, the right measures are to be executed at the right time. This dissertation deals with a description of the railway track condition. A bottom-up approach provides an in-depth assessment of track using a variety of measurement signals and an aggregated component-specific assessment. Since the approach is based on well positioned measurement signals, it is valid for monitoring specific track sections as well as whole networks. Innovative analyses of various measurement signals form a sound basis to grasp their characteristics enabling a component specific condition evaluation of railway track. The use of historical measurement data allows for an analysis of track behaviour over time. A thorough validation process, including on-site inspections and excavations, shows that the presented approach is able to evaluate the actual condition of railway track. The assessment of the specific components condition can be used for timely maintenance as well as renewal planning. Based on correlation analyses, the component specific evaluations are aggregated into one holistic quality figure. This enables asset managers to monitor the asset condition network-wide as well as to predict future budget demands.},
doi = {10.3217/978-3-85125-569-0},
language = {English},
owner = {ofrey},
}
Thesis
-
Muhammad Adnan Siddique.
SAR tomography as an add-on to persistent scatterer interferometry for improved deformation coverage.
PhD thesis,
ETH Zurich,
2018.
Keyword(s): SAR Processing,
SAR Tomography,
deformation analysis in urban and alpine areas,
persistent scatterer interferometry,
PSI,
atmospheric phase corrections,
radar interferometry,
differential SAR tomography,
SAR interferometry,
InSAR,
SAR,
SAR tomography,
Synthetic aperture radar (SAR),
deformation,
SAR signal processing,
Radar signal processing,
SAR Interferometry,
InSAR,
interferometric stacking,
persistent scatterer interferometry,
PSI,
spaceborne SAR radar interferometry,
spaceborne radar,
X-Band,
TerraSAR-X,
synthetic aperture radar,
tomography,
3-D point cloud retrieval,
SAR tomography based 3-D point cloud extraction,
high-resolution spaceborne SAR,
Cosmo Skymed,
interferometric stack,
layover scenario case,
persistent scatterer interferometry,
PSI,
point-like scatterer,
processing approach,
Alpine Remote Sensing,
Spaceborne radar,
Synthetic aperture radar,
Three-dimensional displays,
Tomography,
3-D point cloud,
SAR interferometry,
Cosmo SkyMed,
Matter Valley,
Switzerland,
Alps,
mountainous terrain,
layover.
Abstract: Persistent scatterer interferometry (PSI) is a synthetic aperture radar (SAR) signal processing technique for the measurement of land surface deformation. As a conceptual derivative of differential interferometry, it strives to extract the interferometric phase variation induced by the line-of-sight component of the deformation. PSI limits the interferometric analysis to the so-called {persistent} (or synonymously {coherent}) scatterers (PS). These are single dominant scatterers exhibiting point-like, quasi-deterministic behavior. On the one hand, it implies reduced susceptibility to temporal and geometric decorrelation, but on the other hand, it incurs the limitation that range-azimuth resolution cells containing multiple scatterers are rejected in the PSI processing, even if they are individually coherent. Side-looking geometry of SAR sensors results in frequent layovers, whereby multiple scatterers situated at different elevations fall in the same resolution cell. Consequently, deformation coverage with PSI processing may remain limited in layover-affected areas. SAR tomography is a means to alleviate the aforementioned limitation. It allows 3-D reconstruction of the scene reflectivity -- a feature that offers the potential to resolve the layover problem. The coherent scatterers that are interfering in the same cell can be separated along the elevation. Additionally, differential SAR tomographic methods allow a joint spatio-temporal inversion of the coherent scatterers in layover, i.e., the position along the elevation axis as well as the deformation velocity of the interfering scatterers are simultaneously estimated. Therefore, differential SAR tomography can be used as an add-on to PSI techniques to improve deformation coverage in layover-affected areas. This dissertation provides a comprehensive assessment of the utility offered by SAR tomography as an add-on to PSI. Several aspects of a tomographic processing framework, such as different phase models for tomography, phase calibration of the interferometric stack, statistical detection of coherent scatterers, etc., need to be investigated. To this end, three core investigations have been performed. In each case, a prior PSI solution has been used as a starting point. It serves not only as a reference to compare with, but is also shown to be a natural precursor to tomographic processing. An interferometric data stack comprising 50 TerraSAR-X stripmap-mode acquisitions over an urban zone in the city of Barcelona, Spain, has been used in the first investigation. The phase models for classical SAR tomography (3-D SAR), differential tomography with the assumption of linear deformation over time, and the one further extended to simultaneously model thermal expansion, are compared against each other with respect to their suitability in resolving layovers. The results confirm that modeling thermal expansion of the scatterers, in addition to linear deformation and elevation, is indeed critical for effective layover separations, especially in the case of high-rise buildings. The quality of the scatterers obtained with tomography has been evaluated in terms of the dispersion of the residual phase and compared against the quality of the PS identified in the prior PSI processing. The results show a trade-off between the quantity and the quality of the scatterers. The second investigation focuses on the problem of phase calibration for a potential application of SAR tomography in mountainous regions. It is a case study that assesses a regression-kriging approach to functionally model height-dependent atmospheric phase variations and lateral phase trends, and consider the turbulent mixing effects in a stochastic sense. The study has been performed on a stack comprising 32 Cosmo-SkyMed acquisitions over Matter Valley in the Swiss Alps. Phase corrections with the kriging approach extend the deformation coverage to parts of a mountainside (in layover) where no PS were identified in the prior PSI processing. However, a very few double scatterers are detected on the whole. The third investigation explores how to perform scatterer detection for tomography extending the same quality considerations as used in the prior PSI processing. The outcome of this work is a detection strategy whereby quality parameters (in terms of the statistics of the phase residue or ensemble coherence) are used to determine the thresholds for hypothesis testing. The detection strategy is tested on the same data stack as for the first investigation to detect single and double scatterers in an urban area. An empirical analysis of the probability of false alarm is also provided. As a whole, this dissertation covers several aspects that collectively highlight how the synergistic use of PSI and tomography can lead to improved deformation coverage. @PhdThesis{phdThesisSiddiqueETH2018TomoSARasAddOnToPSI, author = {Siddique, Muhammad Adnan}, school = {ETH Zurich}, title = {{SAR} tomography as an add-on to persistent scatterer interferometry for improved deformation coverage}, year = {2018}, abstract = {Persistent scatterer interferometry (PSI) is a synthetic aperture radar (SAR) signal processing technique for the measurement of land surface deformation. As a conceptual derivative of differential interferometry, it strives to extract the interferometric phase variation induced by the line-of-sight component of the deformation. PSI limits the interferometric analysis to the so-called {persistent} (or synonymously {coherent}) scatterers (PS). These are single dominant scatterers exhibiting point-like, quasi-deterministic behavior. On the one hand, it implies reduced susceptibility to temporal and geometric decorrelation, but on the other hand, it incurs the limitation that range-azimuth resolution cells containing multiple scatterers are rejected in the PSI processing, even if they are individually coherent. Side-looking geometry of SAR sensors results in frequent layovers, whereby multiple scatterers situated at different elevations fall in the same resolution cell. Consequently, deformation coverage with PSI processing may remain limited in layover-affected areas. SAR tomography is a means to alleviate the aforementioned limitation. It allows 3-D reconstruction of the scene reflectivity -- a feature that offers the potential to resolve the layover problem. The coherent scatterers that are interfering in the same cell can be separated along the elevation. Additionally, differential SAR tomographic methods allow a joint spatio-temporal inversion of the coherent scatterers in layover, i.e., the position along the elevation axis as well as the deformation velocity of the interfering scatterers are simultaneously estimated. Therefore, differential SAR tomography can be used as an add-on to PSI techniques to improve deformation coverage in layover-affected areas. This dissertation provides a comprehensive assessment of the utility offered by SAR tomography as an add-on to PSI. Several aspects of a tomographic processing framework, such as different phase models for tomography, phase calibration of the interferometric stack, statistical detection of coherent scatterers, etc., need to be investigated. To this end, three core investigations have been performed. In each case, a prior PSI solution has been used as a starting point. It serves not only as a reference to compare with, but is also shown to be a natural precursor to tomographic processing. An interferometric data stack comprising 50 TerraSAR-X stripmap-mode acquisitions over an urban zone in the city of Barcelona, Spain, has been used in the first investigation. The phase models for classical SAR tomography (3-D SAR), differential tomography with the assumption of linear deformation over time, and the one further extended to simultaneously model thermal expansion, are compared against each other with respect to their suitability in resolving layovers. The results confirm that modeling thermal expansion of the scatterers, in addition to linear deformation and elevation, is indeed critical for effective layover separations, especially in the case of high-rise buildings. The quality of the scatterers obtained with tomography has been evaluated in terms of the dispersion of the residual phase and compared against the quality of the PS identified in the prior PSI processing. The results show a trade-off between the quantity and the quality of the scatterers. The second investigation focuses on the problem of phase calibration for a potential application of SAR tomography in mountainous regions. It is a case study that assesses a regression-kriging approach to functionally model height-dependent atmospheric phase variations and lateral phase trends, and consider the turbulent mixing effects in a stochastic sense. The study has been performed on a stack comprising 32 Cosmo-SkyMed acquisitions over Matter Valley in the Swiss Alps. Phase corrections with the kriging approach extend the deformation coverage to parts of a mountainside (in layover) where no PS were identified in the prior PSI processing. However, a very few double scatterers are detected on the whole. The third investigation explores how to perform scatterer detection for tomography extending the same quality considerations as used in the prior PSI processing. The outcome of this work is a detection strategy whereby quality parameters (in terms of the statistics of the phase residue or ensemble coherence) are used to determine the thresholds for hypothesis testing. The detection strategy is tested on the same data stack as for the first investigation to detect single and double scatterers in an urban area. An empirical analysis of the probability of false alarm is also provided. As a whole, this dissertation covers several aspects that collectively highlight how the synergistic use of PSI and tomography can lead to improved deformation coverage.}, doi = {10.3929/ethz-b-000299241}, file = {:phdThesisSiddiqueETH2018TomoSARasAddOnToPSI.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, deformation analysis in urban and alpine areas; persistent scatterer interferometry, PSI; atmospheric phase corrections; radar interferometry; differential SAR tomography; SAR interferometry, InSAR; SAR; SAR tomography; Synthetic aperture radar (SAR); deformation; SAR signal processing; Radar signal processing, SAR Interferometry, InSAR, interferometric stacking;persistent scatterer interferometry; PSI, spaceborne SAR radar interferometry;spaceborne radar; X-Band, TerraSAR-X, synthetic aperture radar;tomography;3-D point cloud retrieval; SAR tomography based 3-D point cloud extraction; high-resolution spaceborne SAR, Cosmo Skymed, interferometric stack;layover scenario case;persistent scatterer interferometry; PSI, point-like scatterer;processing approach;Alpine Remote Sensing; Spaceborne radar;Synthetic aperture radar;Three-dimensional displays;Tomography; 3-D point cloud;SAR interferometry, Cosmo SkyMed, Matter Valley, Switzerland, Alps, mountainous terrain, layover, layover separation}, owner = {ofrey}, }
Articles in journal or book chapters
-
F. Alshawaf,
F. Zus,
K. Balidakis,
Z. Deng,
M. Hoseini,
G. Dick,
and J. Wickert.
On the Statistical Significance of Climatic Trends Estimated From GPS Tropospheric Time Series.
Journal of Geophysical Research: Atmospheres,
123(19):10,967-10,990,
2018.
Note: Cited By 17.
@ARTICLE{Alshawaf201810967, author={Alshawaf, F. and Zus, F. and Balidakis, K. and Deng, Z. and Hoseini, M. and Dick, G. and Wickert, J.}, title={On the Statistical Significance of Climatic Trends Estimated From GPS Tropospheric Time Series}, journal={Journal of Geophysical Research: Atmospheres}, year={2018}, volume={123}, number={19}, pages={10,967-10,990}, doi={10.1029/2018JD028703}, note={cited By 17}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055412778&doi=10.1029%2f2018JD028703&partnerID=40&md5=9f48b9f92b4bcab6a2002809dbf374f2}, document_type={Article}, source={Scopus}, } -
Homa Ansari,
Francesco De Zan,
and Richard Bamler.
Efficient Phase Estimation for Interferogram Stacks.
IEEE Transactions on Geoscience and Remote Sensing,
56(7):4109-4125,
July 2018.
Keyword(s): maximum likelihood estimation,
phase estimation,
radar interferometry,
remote sensing by radar,
synthetic aperture radar,
terrain mapping,
time series,
efficient phase estimation,
interferogram stacks,
signal decorrelation,
SAR interferometry,
high-precision deformation,
different techniques,
short baseline subset,
SqueeSAR,
CAESAR,
overarching schemes,
different analysis approaches,
deformation estimation,
called Eigendecomposition,
maximum-likelihood-estimator,
Interferometric phase,
state-of-the-art techniques,
computational estimation efficiency,
Sequential Estimator,
efficient processing scheme,
state-of-the-art approaches,
Electromagnetic interference,
Time series analysis,
Maximum likelihood estimation,
Systematics,
Synthetic aperture radar,
Strain,
Big Data,
coherence matrix,
covariance estimation,
differential interferometric synthetic aperture radar,
distributed scatterers (DS),
efficiency,
error analysis,
maximum-likelihood estimation,
near real-time (NRT) processing.
Abstract: SAR Processin, Signal decorrelation poses a limitation to multipass SAR interferometry. In pursuit of overcoming this limitation to achieve high-precision deformation estimates, different techniques have been developed, with short baseline subset, SqueeSAR, and CAESAR as the overarching schemes. These different analysis approaches raise the question of their efficiency and limitation in phase and consequently deformation estimation. This contribution first addresses this question and then proposes a new estimator with improved performance, called Eigendecomposition-based Maximum-likelihood-estimator of Interferometric phase (EMI). The proposed estimator combines the advantages of the state-of-the-art techniques. Identical to CAESAR, EMI is solved using eigendecomposition; it is therefore computationally efficient and straightforward in implementation. Similar to SqueeSAR, EMI is a maximum-likelihood-estimator; hence, it retains estimation efficiency. The computational and estimation efficiency of EMI renders it as an optimum choice for phase estimation. A further marriage of EMI with the proposed Sequential Estimator by Ansari et al. provides an efficient processing scheme tailored to the analysis of Big InSAR Data. EMI is formulated and verified in relation to the state-of-the-art approaches via mathematical formulation, simulation analysis, and experiments with time series of Sentinel-1 data over the volcanic island of Vulcano, Italy. @Article{ansariDeZanBamlerTGRS2018EfficientPhaseEstimationInSARStacks, author = {Ansari, Homa and De Zan, Francesco and Bamler, Richard}, title = {Efficient Phase Estimation for Interferogram Stacks}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, year = {2018}, volume = {56}, number = {7}, pages = {4109-4125}, month = {July}, abstract = {SAR Processin, Signal decorrelation poses a limitation to multipass SAR interferometry. In pursuit of overcoming this limitation to achieve high-precision deformation estimates, different techniques have been developed, with short baseline subset, SqueeSAR, and CAESAR as the overarching schemes. These different analysis approaches raise the question of their efficiency and limitation in phase and consequently deformation estimation. This contribution first addresses this question and then proposes a new estimator with improved performance, called Eigendecomposition-based Maximum-likelihood-estimator of Interferometric phase (EMI). The proposed estimator combines the advantages of the state-of-the-art techniques. Identical to CAESAR, EMI is solved using eigendecomposition; it is therefore computationally efficient and straightforward in implementation. Similar to SqueeSAR, EMI is a maximum-likelihood-estimator; hence, it retains estimation efficiency. The computational and estimation efficiency of EMI renders it as an optimum choice for phase estimation. A further marriage of EMI with the proposed Sequential Estimator by Ansari et al. provides an efficient processing scheme tailored to the analysis of Big InSAR Data. EMI is formulated and verified in relation to the state-of-the-art approaches via mathematical formulation, simulation analysis, and experiments with time series of Sentinel-1 data over the volcanic island of Vulcano, Italy.}, doi = {10.1109/TGRS.2018.2826045}, file = {:ansariDeZanBamlerTGRS2018EfficientPhaseEstimationInSARStacks.pdf:PDF}, keywords = {maximum likelihood estimation;phase estimation;radar interferometry;remote sensing by radar;synthetic aperture radar;terrain mapping;time series;efficient phase estimation;interferogram stacks;signal decorrelation;SAR interferometry;high-precision deformation;different techniques;short baseline subset;SqueeSAR;CAESAR;overarching schemes;different analysis approaches;deformation estimation;called Eigendecomposition;maximum-likelihood-estimator;Interferometric phase;state-of-the-art techniques;computational estimation efficiency;Sequential Estimator;efficient processing scheme;state-of-the-art approaches;Electromagnetic interference;Time series analysis;Maximum likelihood estimation;Systematics;Synthetic aperture radar;Strain;Big Data;coherence matrix;covariance estimation;differential interferometric synthetic aperture radar;distributed scatterers (DS);efficiency;error analysis;maximum-likelihood estimation;near real-time (NRT) processing}, } -
Simone Baffelli,
Othmar Frey,
Charles L. Werner,
and Irena Hajnsek.
Polarimetric Calibration of the Ku-Band Advanced Polarimetric Radar Interferometer.
IEEE Trans. Geosci. Remote Sens.,
56(4):2295-2311,
2018.
Keyword(s): real-aperture radar,
radar,
terrestrial radar,
Apertures,
Calibration,
interferometry,
radar interferometry,
Radar antennas,
Radar imaging,
Radar polarimetry,
ground-based radar,
polarimetric calibration,
polarimetric,
GB-RADAR,
polarimetric-interferometric radar,
Gamma Portable Radar Interferometer,
GPRI.
Abstract: Differential interferometry using ground-based radar systems permits to monitor displacements in natural terrain with high flexibility in location, time of acquisition, and revisit time. In combination with polarimetric imaging, discrimination of different scattering mechanisms present in a resolution cell can be obtained simultaneously with the estimation of surface displacement. In this paper, we present the preprocessing steps and the calibration procedure required to produce high-quality calibrated polarimetric single-look complex imagery with KAPRI, a new portable Ku-band polarimetric radar interferometer. The processing of KAPRI data into single look complex images is addressed, including the correction of beam squint and of azimuthal phase variations. A polarimetric calibration model adapted to the acquisition mode is presented and used to produce calibrated polarimetric covariance matrix data. The methods are validated by means of a scene containing five trihedral corner reflectors. Data preprocessing is assessed by analyzing the oversampled response of a corner reflector, and the polarimetric calibration quality is verified by computing polarimetric signatures and residual calibration parameters. @Article{baffelliFreyWernerHajnsekTGRS2018PolGPRICalibration, author = {Baffelli, Simone and Frey, Othmar and Werner, Charles L. and Hajnsek, Irena}, title = {Polarimetric Calibration of the {Ku}-Band Advanced Polarimetric Radar Interferometer}, journal = {IEEE Trans. Geosci. Remote Sens.}, year = {2018}, volume = {56}, number = {4}, pages = {2295-2311}, issn = {1558-0644}, abstract = {Differential interferometry using ground-based radar systems permits to monitor displacements in natural terrain with high flexibility in location, time of acquisition, and revisit time. In combination with polarimetric imaging, discrimination of different scattering mechanisms present in a resolution cell can be obtained simultaneously with the estimation of surface displacement. In this paper, we present the preprocessing steps and the calibration procedure required to produce high-quality calibrated polarimetric single-look complex imagery with KAPRI, a new portable Ku-band polarimetric radar interferometer. The processing of KAPRI data into single look complex images is addressed, including the correction of beam squint and of azimuthal phase variations. A polarimetric calibration model adapted to the acquisition mode is presented and used to produce calibrated polarimetric covariance matrix data. The methods are validated by means of a scene containing five trihedral corner reflectors. Data preprocessing is assessed by analyzing the oversampled response of a corner reflector, and the polarimetric calibration quality is verified by computing polarimetric signatures and residual calibration parameters.}, doi = {10.1109/TGRS.2017.2778049}, file = {:baffelliFreyWernerHajnsekTGRS2018PolGPRICalibration.pdf:PDF}, keywords = {real-aperture radar, radar, terrestrial radar, Apertures, Calibration, interferometry, radar interferometry, Radar antennas, Radar imaging, Radar polarimetry, ground-based radar, polarimetric calibration, polarimetric, GB-RADAR, polarimetric-interferometric radar, Gamma Portable Radar Interferometer, GPRI}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/baffelliFreyWernerHajnsekTGRS2018PolGPRICalibration.pdf}, url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8226855}, } -
Alessandra Budillon,
Michele Crosetto,
Angel Caroline Johnsy,
Oriol Monserrat,
Vrinda Krishnakumar,
and Gilda Schirinzi.
Comparison of Persistent Scatterer Interferometry and SAR Tomography Using Sentinel-1 in Urban Environment.
Remote Sensing,
10(12),
2018.
Keyword(s): SAR Processing,
SAR Tomography,
Tomography,
3D SAR data imaging,
Persistent Scatterer Interferometry,
PSI,
Interferometry,
SAR Interferometry,
differential interferometry,
DInSAR.
Abstract: In this paper, persistent scatterer interferometry and Synthetic Aperture Radar (SAR) tomography have been applied to Sentinel-1 data for urban monitoring. The paper analyses the applicability of SAR tomography to Sentinel-1 data, which is not granted, due to the reduced range and azimuth resolutions and the low resolution in elevation. In a first part of the paper, two implementations of the two techniques are described. In the experimental part, the two techniques are used in parallel to process the same Sentinel-1 data over two test areas. An intercomparison of the results from persistent scatterer interferometry and SAR tomography is carried out, comparing the main parameters estimated by the two techniques. Finally, the paper addresses the complementarity of the two techniques, and in particular it assesses the increase of measurement density that can be achieved by adding the double scatterers from SAR tomography to the persistent scatterer interferometry measurements. @Article{budillonCrosettoJohnsyMonserratKrishnakumarSchirinziRemoteSensing2018ComparisonPSIandTomoWithSentinel1Urban, author = {Budillon, Alessandra and Crosetto, Michele and Johnsy, Angel Caroline and Monserrat, Oriol and Krishnakumar, Vrinda and Schirinzi, Gilda}, journal = {Remote Sensing}, title = {Comparison of Persistent Scatterer Interferometry and {SAR} Tomography Using {Sentinel-1} in Urban Environment}, year = {2018}, issn = {2072-4292}, number = {12}, volume = {10}, abstract = {In this paper, persistent scatterer interferometry and Synthetic Aperture Radar (SAR) tomography have been applied to Sentinel-1 data for urban monitoring. The paper analyses the applicability of SAR tomography to Sentinel-1 data, which is not granted, due to the reduced range and azimuth resolutions and the low resolution in elevation. In a first part of the paper, two implementations of the two techniques are described. In the experimental part, the two techniques are used in parallel to process the same Sentinel-1 data over two test areas. An intercomparison of the results from persistent scatterer interferometry and SAR tomography is carried out, comparing the main parameters estimated by the two techniques. Finally, the paper addresses the complementarity of the two techniques, and in particular it assesses the increase of measurement density that can be achieved by adding the double scatterers from SAR tomography to the persistent scatterer interferometry measurements.}, article-number = {1986}, doi = {10.3390/rs10121986}, file = {:budillonCrosettoJohnsyMonserratKrishnakumarSchirinziRemoteSensing2018ComparisonPSIandTomoWithSentinel1Urban.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, Tomography, 3D SAR data imaging;Persistent Scatterer Interferometry, PSI, Interferometry, SAR Interferometry, differential interferometry, DInSAR}, owner = {ofrey}, url = {http://www.mdpi.com/2072-4292/10/12/1986}, } -
Ning Cao,
Hyongki Lee,
Evan Zaugg,
Ramesh Shrestha,
William E. Carter,
Craig Glennie,
Zhong Lu,
and Hanwen Yu.
Estimation of Residual Motion Errors in Airborne SAR Interferometry Based on Time-Domain Backprojection and Multisquint Techniques.
IEEE Trans. Geosci. Remote Sens.,
56(4):2397-2407,
2018.
Keyword(s): SAR Processing,
Interferometry,
SAR Interferometry,
InSAR,
Differential SAR Interferometry,
DInSAR,
deformation monitoring,
subsidence monitoring,
Displacement,
Focusing,
Radar antennas,
Synthetic aperture radar,
Time-domain analysis,
Trajectory,
Backprojection (BP),
SAR interferometry (InSAR),
motion compensation (MoCo),
residual motion error (RME),
synthetic aperture radar (SAR).
Abstract: For airborne repeat-pass synthetic aperture radar interferometry (InSAR), precise trajectory information is needed to compensate for deviations of the platform movement from a linear track. Using the trajectory information, motion compensation (MoCo) can be implemented within SAR data focusing. Due to the inaccuracy of current navigation systems, residual motion errors (RMEs) exist between the real and measured trajectory, causing phase undulations in the final interferograms. Up to now, MoCo and RME estimation have usually been combined in airborne InSAR to estimate ground deformation. Conventional MoCo methods generally involve azimuthal and range resampling and phase correction. Then frequency-domain focusing techniques can be used to generate the SAR images. After focusing SAR images with MoCo, both multisquint and autofocus approaches can be used to estimate RME. In addition to the MoCo-based frequency-domain focusing, the time-domain backprojection (BP) technique can also focus the SAR data obtained from highly nonlinear platform trajectories. In this paper, we present, for the first time, the combination of BP and multisquint techniques for RME estimation. A detailed derivation of the implementation of the multisquint approach using the BP-focusing images is presented. Repeat-pass data from the SlimSAR system over Slumgullion landslide are used to demonstrate the feasibility of RME estimation for both stationary and nonstationary scenes. We conclude that the proposed method can effectively remove the RME. @Article{caoLeeZauggShresthaCarterGlennieLuYuTGRS2018TDBPResidualMotionInSAR, author = {Cao, Ning and Lee, Hyongki and Zaugg, Evan and Shrestha, Ramesh and Carter, William E. and Glennie, Craig and Lu, Zhong and Yu, Hanwen}, journal = {IEEE Trans. Geosci. Remote Sens.}, title = {Estimation of Residual Motion Errors in Airborne {SAR} Interferometry Based on Time-Domain Backprojection and Multisquint Techniques}, year = {2018}, issn = {0196-2892}, number = {4}, pages = {2397-2407}, volume = {56}, abstract = {For airborne repeat-pass synthetic aperture radar interferometry (InSAR), precise trajectory information is needed to compensate for deviations of the platform movement from a linear track. Using the trajectory information, motion compensation (MoCo) can be implemented within SAR data focusing. Due to the inaccuracy of current navigation systems, residual motion errors (RMEs) exist between the real and measured trajectory, causing phase undulations in the final interferograms. Up to now, MoCo and RME estimation have usually been combined in airborne InSAR to estimate ground deformation. Conventional MoCo methods generally involve azimuthal and range resampling and phase correction. Then frequency-domain focusing techniques can be used to generate the SAR images. After focusing SAR images with MoCo, both multisquint and autofocus approaches can be used to estimate RME. In addition to the MoCo-based frequency-domain focusing, the time-domain backprojection (BP) technique can also focus the SAR data obtained from highly nonlinear platform trajectories. In this paper, we present, for the first time, the combination of BP and multisquint techniques for RME estimation. A detailed derivation of the implementation of the multisquint approach using the BP-focusing images is presented. Repeat-pass data from the SlimSAR system over Slumgullion landslide are used to demonstrate the feasibility of RME estimation for both stationary and nonstationary scenes. We conclude that the proposed method can effectively remove the RME.}, doi = {10.1109/TGRS.2017.2779852}, file = {:caoLeeZauggShresthaCarterGlennieLuYuTGRS2018TDBPResidualMotionInSAR.pdf:PDF}, keywords = {SAR Processing, Interferometry, SAR Interferometry, InSAR, Differential SAR Interferometry, DInSAR, deformation monitoring, subsidence monitoring, Displacement, Focusing, Radar antennas, Synthetic aperture radar, Time-domain analysis, Trajectory, Backprojection (BP), SAR interferometry (InSAR), motion compensation (MoCo), residual motion error (RME), synthetic aperture radar (SAR)}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/caoLeeZauggShresthaCarterGlennieLuYuTGRS2018TDBPResidualMotionInSAR.pdf}, } -
Cosmin Danisor,
Gianfranco Fornaro,
Antonio Pauciullo,
Diego Reale,
and Mihai Datcu.
Super-Resolution Multi-Look Detection in SAR Tomography.
Remote Sensing,
10(12),
2018.
Keyword(s): SAR Processing,
SAR Tomography,
Multi-look,
Coherence,
Detectors,
Interferometry,
Spatial resolution,
Synthetic aperture radar,
Tomography,
Detection,
SAR tomography,
generalized likelihood ratio test,
multi-look,
persistent scatterers (PSs),
GLRT,
Super-resolution,
Capon,
Generalized likelihood ratio test.
Abstract: Synthetic Aperture Radar (SAR) Tomography (TomoSAR) allows extending the 2-D focusing capabilities of SAR to the elevation direction, orthogonal to the azimuth and range. The multi-dimensional extension (along the time) also enables the monitoring of possible scatterer displacements. A key aspect of TomoSAR is the identification, in the presence of noise, of multiple persistent scatterers interfering within the same 2-D (azimuth range plane) pixel. To this aim, the use of multi-look has been shown to provide tangible improvements in the detection of single and double interfering persistent scatterers at the expense of a minor spatial resolution loss. Depending on the system acquisition characteristics, this operation may require also the detection of multiple scatterers interfering at distances lower than the Rayleigh resolution (super-resolution). In this work we further investigated the use of multi-look in TomoSAR for the detection of multiple scatterers located also below the Rayleigh resolution. A solution relying on the Capon filtering was first analyzed, due to its improved capabilities in the separation of the responses of multiple scatterers and sidelobe suppression. Moreover, in the framework of the Generalized Likelihood Ratio Test (GLRT), the single-look support based detection strategy recently proposed in the literature was extended to the multi-look case. Experimental results of tests carried out on two datasets acquired by TerraSAR-X and COSMO-SkyMED sensors are provided to show the performances of the proposed solution as well as the effects of the baseline span of the dataset for the detection capabilities of interfering scatterers. @Article{danisorFornaroPauciulloRealeDatcuRemoteSensing2018SuperResMLDetectionSARTomo, author = {Danisor, Cosmin and Fornaro, Gianfranco and Pauciullo, Antonio and Reale, Diego and Datcu, Mihai}, journal = {Remote Sensing}, title = {Super-Resolution Multi-Look Detection in {SAR} Tomography}, year = {2018}, issn = {2072-4292}, number = {12}, volume = {10}, abstract = {Synthetic Aperture Radar (SAR) Tomography (TomoSAR) allows extending the 2-D focusing capabilities of SAR to the elevation direction, orthogonal to the azimuth and range. The multi-dimensional extension (along the time) also enables the monitoring of possible scatterer displacements. A key aspect of TomoSAR is the identification, in the presence of noise, of multiple persistent scatterers interfering within the same 2-D (azimuth range plane) pixel. To this aim, the use of multi-look has been shown to provide tangible improvements in the detection of single and double interfering persistent scatterers at the expense of a minor spatial resolution loss. Depending on the system acquisition characteristics, this operation may require also the detection of multiple scatterers interfering at distances lower than the Rayleigh resolution (super-resolution). In this work we further investigated the use of multi-look in TomoSAR for the detection of multiple scatterers located also below the Rayleigh resolution. A solution relying on the Capon filtering was first analyzed, due to its improved capabilities in the separation of the responses of multiple scatterers and sidelobe suppression. Moreover, in the framework of the Generalized Likelihood Ratio Test (GLRT), the single-look support based detection strategy recently proposed in the literature was extended to the multi-look case. Experimental results of tests carried out on two datasets acquired by TerraSAR-X and COSMO-SkyMED sensors are provided to show the performances of the proposed solution as well as the effects of the baseline span of the dataset for the detection capabilities of interfering scatterers.}, article-number = {1894}, doi = {10.3390/rs10121894}, file = {:danisorFornaroPauciulloRealeDatcuRemoteSensing2018SuperResMLDetectionSARTomo.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, Multi-look, Coherence;Detectors;Interferometry;Spatial resolution;Synthetic aperture radar;Tomography;Detection;SAR tomography;generalized likelihood ratio test;multi-look;persistent scatterers (PSs), GLRT, Super-resolution, Capon, Generalized likelihood ratio test}, owner = {ofrey}, url = {http://www.mdpi.com/2072-4292/10/12/1894}, } -
Markus Even and Karsten Schulz.
InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances.
Remote Sensing,
10(5),
2018.
Keyword(s): SAR Processing,
Interferometry,
SAR Interferometry,
InSAR,
Persistent Scatterers,
Persistent Scatterer Interferometry,
PSI,
Distributed Scatterers,
Distributed Scatterer Interferometry,
DS,
DS Interferoemetry,
preprocessing,
adaptive neighborhood,
covariance,
coherence,
deformation,
displacement mapping,
deformation monitoring,
SqueeSAR.
Abstract: Interferometric Synthetic Aperture Radar (InSAR) is a powerful remote sensing technique able to measure deformation of the earth’s surface over large areas. InSAR deformation analysis uses two main categories of backscatter: Persistent Scatterers (PS) and Distributed Scatterers (DS). While PS are characterized by a high signal-to-noise ratio and predominantly occur as single pixels, DS possess a medium or low signal-to-noise ratio and can only be exploited if they form homogeneous groups of pixels that are large enough to allow for statistical analysis. Although DS have been used by InSAR since its beginnings for different purposes, new methods developed during the last decade have advanced the field significantly. Preprocessing of DS with spatio-temporal filtering allows today the use of DS in PS algorithms as if they were PS, thereby enlarging spatial coverage and stabilizing algorithms. This review explores the relations between different lines of research and discusses open questions regarding DS preprocessing for deformation analysis. The review is complemented with an experiment that demonstrates that significantly improved results can be achieved for preprocessed DS during parameter estimation if their statistical properties are used. @Article{evenSchulzRemoteSensing2018InSARDistributedScatterers, author = {Even, Markus and Schulz, Karsten}, title = {{InSAR} Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances}, journal = {Remote Sensing}, year = {2018}, volume = {10}, number = {5}, issn = {2072-4292}, abstract = {Interferometric Synthetic Aperture Radar (InSAR) is a powerful remote sensing technique able to measure deformation of the earth’s surface over large areas. InSAR deformation analysis uses two main categories of backscatter: Persistent Scatterers (PS) and Distributed Scatterers (DS). While PS are characterized by a high signal-to-noise ratio and predominantly occur as single pixels, DS possess a medium or low signal-to-noise ratio and can only be exploited if they form homogeneous groups of pixels that are large enough to allow for statistical analysis. Although DS have been used by InSAR since its beginnings for different purposes, new methods developed during the last decade have advanced the field significantly. Preprocessing of DS with spatio-temporal filtering allows today the use of DS in PS algorithms as if they were PS, thereby enlarging spatial coverage and stabilizing algorithms. This review explores the relations between different lines of research and discusses open questions regarding DS preprocessing for deformation analysis. The review is complemented with an experiment that demonstrates that significantly improved results can be achieved for preprocessed DS during parameter estimation if their statistical properties are used.}, doi = {10.3390/rs10050744}, file = {:evenSchulzRemoteSensing2018InSARDistributedScatterers.pdf:PDF}, keywords = {SAR Processing, Interferometry, SAR Interferometry, InSAR; Persistent Scatterers; Persistent Scatterer Interferometry, PSI, Distributed Scatterers; Distributed Scatterer Interferometry, DS, DS Interferoemetry, preprocessing; adaptive neighborhood; covariance; coherence; deformation, displacement mapping, deformation monitoring, SqueeSAR}, owner = {ofrey}, url = {http://www.mdpi.com/2072-4292/10/5/744}, } -
Patrick Henkel,
Franziska Koch,
Florian Appel,
Heike Bach,
Monika Prasch,
Lino Schmid,
J�rg Schweizer,
and Wolfram Mauser.
Snow Water Equivalent of Dry Snow Derived From GNSS Carrier Phases.
IEEE Transactions on Geoscience and Remote Sensing,
56(6):3561-3572,
June 2018.
Keyword(s): GNSS,
Snow water equivalent,
SWE,
Davos,
Weissfluhjoch.
Abstract: Snow water equivalent (SWE) is a key variable for various hydrological applications. It is defined as the depth of water that would result upon complete melting of a mass of snow. However, until now, continuous measurements of the SWE are either scarce, expensive, labor-intense, or lack temporal or spatial resolution especially in mountainous and remote regions. We derive the SWE for dry-snow conditions using carrier phase measurements from the Global Navigation Satellite System (GNSS) receivers. Two static GNSS receivers are used, whereby one antenna is placed below the snow and the other antenna is placed above the snow. The carrier phase measurements of both receivers are combined in double differences (DDs) to eliminate clock offsets and phase biases and to mitigate atmospheric errors. Each DD carrier phase measurement depends on the relative position between both antennas, an integer ambiguity due to the periodic nature of the carrier phase signal, and the SWE projected into the direction of incidence. The relative positions of the antennas are determined under snow-free conditions with millimeter accuracy using real-time kinematic positioning. Subsequently, the SWE and carrier phase integer ambiguities are jointly estimated with an integer least-squares estimator. We tested our method at an Alpine test site in Switzerland during the dry-snow season 2015-2016. The SWE derived solely by the GNSS shows very high correlation with conventionally measured snow pillow (root mean square error: 11 mm) and manual snow pit data. This method can be applied to dense low-cost GNSS receiver networks to improve the spatial and temporal information on snow. @Article{henkelKochAppelBachPraschSchmidSchweizerMauserTGRS2018SWEofDrySnowFromGNSSCarrierPhases, author = {Henkel, Patrick and Koch, Franziska and Appel, Florian and Bach, Heike and Prasch, Monika and Schmid, Lino and Schweizer, J�rg and Mauser, Wolfram}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, title = {Snow Water Equivalent of Dry Snow Derived From {GNSS} Carrier Phases}, year = {2018}, issn = {1558-0644}, month = {June}, number = {6}, pages = {3561-3572}, volume = {56}, abstract = {Snow water equivalent (SWE) is a key variable for various hydrological applications. It is defined as the depth of water that would result upon complete melting of a mass of snow. However, until now, continuous measurements of the SWE are either scarce, expensive, labor-intense, or lack temporal or spatial resolution especially in mountainous and remote regions. We derive the SWE for dry-snow conditions using carrier phase measurements from the Global Navigation Satellite System (GNSS) receivers. Two static GNSS receivers are used, whereby one antenna is placed below the snow and the other antenna is placed above the snow. The carrier phase measurements of both receivers are combined in double differences (DDs) to eliminate clock offsets and phase biases and to mitigate atmospheric errors. Each DD carrier phase measurement depends on the relative position between both antennas, an integer ambiguity due to the periodic nature of the carrier phase signal, and the SWE projected into the direction of incidence. The relative positions of the antennas are determined under snow-free conditions with millimeter accuracy using real-time kinematic positioning. Subsequently, the SWE and carrier phase integer ambiguities are jointly estimated with an integer least-squares estimator. We tested our method at an Alpine test site in Switzerland during the dry-snow season 2015-2016. The SWE derived solely by the GNSS shows very high correlation with conventionally measured snow pillow (root mean square error: 11 mm) and manual snow pit data. This method can be applied to dense low-cost GNSS receiver networks to improve the spatial and temporal information on snow.}, doi = {10.1109/TGRS.2018.2802494}, file = {:henkelKochAppelBachPraschSchmidSchweizerMauserTGRS2018SWEofDrySnowFromGNSSCarrierPhases.pdf:PDF}, keywords = {GNSS, Snow water equivalent, SWE, Davos, Weissfluhjoch}, } -
P. Hügler,
F. Roos,
M. Schartel,
M. Geiger,
and C. Waldschmidt.
Radar Taking Off: New Capabilities for UAVs.
IEEE Microwave Magazine,
19(7):43-53,
November 2018.
Keyword(s): accelerometers,
aircraft control,
autonomous aerial vehicles,
collision avoidance,
gyroscopes,
mobile robots,
robot vision,
satellite navigation,
sensor fusion,
SLAM (robots),
stability,
stereo image processing,
UAVs,
waypoint flights,
autopilot mode,
stabilization,
localization,
IMUs,
accelerometers-barometric sensors,
Global Navigation Satellite System,
collision avoidance,
vision-based sensors,
monocular vision,
stereo vision,
radar sensors,
multichannel radar,
unmanned aerial vehicles,
inertial measurement units,
gyroscopes,
flying sensor platforms,
Radar imaging,
Radar measurements,
Radar antennas,
Collision avoidance,
Radar detection,
Transmitters.
Abstract: Modern consumer and industrial unmanned aerial vehicles (UAVs) are easy-to-use flying sensor platforms. They offer stable flight, good maneuverability, hovering, and even waypoint flights in autopilot mode. For stabilization and localization, sensors such as inertial measurement units (IMUs)-including gyroscopes and accelerometers-barometric sensors, and the Global Navigation Satellite System (GNSS) are used. To sense the UAV's direct environment, e.g., for collision avoidance or fully automated flight, additional sensors are needed. State-of-the-art combinations of infrared, ultrasonic, and vision-based sensors (monocular and/or stereo vision) capture the close vicinity. Using radar sensors is advantageous, as they are able to directly sense range and velocity and are not affected by lighting conditions and contrast. With the help of a multichannel radar, the angular information may also be extracted. @Article{huglerRoosSchartelGeigerWaldschmidtIEEEMicrowaveMag2018RadarOnUAVs, author = {P. {H\"ugler} and F. {Roos} and M. {Schartel} and M. {Geiger} and C. {Waldschmidt}}, title = {Radar Taking Off: New Capabilities for {UAVs}}, journal = {IEEE Microwave Magazine}, year = {2018}, volume = {19}, number = {7}, pages = {43-53}, month = {Nov}, issn = {1557-9581}, abstract = {Modern consumer and industrial unmanned aerial vehicles (UAVs) are easy-to-use flying sensor platforms. They offer stable flight, good maneuverability, hovering, and even waypoint flights in autopilot mode. For stabilization and localization, sensors such as inertial measurement units (IMUs)-including gyroscopes and accelerometers-barometric sensors, and the Global Navigation Satellite System (GNSS) are used. To sense the UAV's direct environment, e.g., for collision avoidance or fully automated flight, additional sensors are needed. State-of-the-art combinations of infrared, ultrasonic, and vision-based sensors (monocular and/or stereo vision) capture the close vicinity. Using radar sensors is advantageous, as they are able to directly sense range and velocity and are not affected by lighting conditions and contrast. With the help of a multichannel radar, the angular information may also be extracted.}, doi = {10.1109/MMM.2018.2862558}, file = {:huglerRoosSchartelGeigerWaldschmidtIEEEMicrowaveMag2018RadarOnUAVs.pdf:PDF}, keywords = {accelerometers;aircraft control;autonomous aerial vehicles;collision avoidance;gyroscopes;mobile robots;robot vision;satellite navigation;sensor fusion;SLAM (robots);stability;stereo image processing;UAVs;waypoint flights;autopilot mode;stabilization;localization;IMUs;accelerometers-barometric sensors;Global Navigation Satellite System;collision avoidance;vision-based sensors;monocular vision;stereo vision;radar sensors;multichannel radar;unmanned aerial vehicles;inertial measurement units;gyroscopes;flying sensor platforms;Radar imaging;Radar measurements;Radar antennas;Collision avoidance;Radar detection;Transmitters}, owner = {ofrey}, } -
R. Jolivet and M. Simons.
A Multipixel Time Series Analysis Method Accounting for Ground Motion, Atmospheric Noise, and Orbital Errors.
Geophysical Research Letters,
45(4):1814-1824,
2018.
Keyword(s): InSAR,
Time Series.
Abstract: Abstract Interferometric synthetic aperture radar time series methods aim to reconstruct time-dependent ground displacements over large areas from sets of interferograms in order to detect transient, periodic, or small-amplitude deformation. Because of computational limitations, most existing methods consider each pixel independently, ignoring important spatial covariances between observations. We describe a framework to reconstruct time series of ground deformation while considering all pixels simultaneously, allowing us to account for spatial covariances, imprecise orbits, and residual atmospheric perturbations. We describe spatial covariances by an exponential decay function dependent of pixel-to-pixel distance. We approximate the impact of imprecise orbit information and residual long-wavelength atmosphere as a low-order polynomial function. Tests on synthetic data illustrate the importance of incorporating full covariances between pixels in order to avoid biased parameter reconstruction. An example of application to the northern Chilean subduction zone highlights the potential of this method. @Article{jolivetSimonsGRL2018MultipixelTimeSeriesAnalysisInSARwithGroundMotionAtmoAndOrbitErrors, author = {Jolivet, R. and Simons, M.}, journal = {Geophysical Research Letters}, title = {A Multipixel Time Series Analysis Method Accounting for Ground Motion, Atmospheric Noise, and Orbital Errors}, year = {2018}, number = {4}, pages = {1814-1824}, volume = {45}, abstract = {Abstract Interferometric synthetic aperture radar time series methods aim to reconstruct time-dependent ground displacements over large areas from sets of interferograms in order to detect transient, periodic, or small-amplitude deformation. Because of computational limitations, most existing methods consider each pixel independently, ignoring important spatial covariances between observations. We describe a framework to reconstruct time series of ground deformation while considering all pixels simultaneously, allowing us to account for spatial covariances, imprecise orbits, and residual atmospheric perturbations. We describe spatial covariances by an exponential decay function dependent of pixel-to-pixel distance. We approximate the impact of imprecise orbit information and residual long-wavelength atmosphere as a low-order polynomial function. Tests on synthetic data illustrate the importance of incorporating full covariances between pixels in order to avoid biased parameter reconstruction. An example of application to the northern Chilean subduction zone highlights the potential of this method.}, doi = {https://doi.org/10.1002/2017GL076533}, eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017GL076533}, file = {:jolivetSimonsGRL2018MultipixelTimeSeriesAnalysisInSARwithGroundMotionAtmoAndOrbitErrors.pdf:PDF}, keywords = {InSAR, Time Series}, owner = {ofrey}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017GL076533}, } -
Heming Liao,
Franz J. Meyer,
Bernd Scheuchl,
Jeremie Mouginot,
Ian Joughin,
and Eric Rignot.
Ionospheric correction of InSAR data for accurate ice velocity measurement at polar regions.
Remote Sensing of Environment,
209:166-180,
2018.
Keyword(s): Synthetic aperture radar,
SAR interferometry,
Ice velocity,
Range split spectrum,
Data stacking,
Ionosphere effect,
Ionosphere correction.
Abstract: Interferometric synthetic aperture radar (InSAR) has become an essential tool for measuring ice sheet velocity in the Polar Regions. At low radar frequencies, e.g. L-band (1.2 GHz) but also at higher frequency, e.g. C-band (5.6 GHz), the ionosphere has been documented to be an important source of noise in these data. In this paper, we employ a split-spectrum technique and investigate its performance for correcting ionospheric effects in InSAR-based ice velocity measurements in Greenland and Antarctica. Three case studies using ALOS PALSAR data are used to assess the performance of the split spectrum technique for ionosphere correction over a range of environmental parameters. We employ several approaches to evaluate the results, including visual inspection, profile analysis, comparison of experimental and theoretic errors, comparison with reference data from other sources, generation of double difference interferograms, and analysis of time series of multi-temporal data. Our experiments show that ionospheric distortions are observed regularly, and in our analyzed Greenland dataset and Antarctic dataset the ionospheric noise reaches 14 m/yr and 10 m/yr, respectively, which exceeds the signal associated with ice motion. Our analysis using several different approaches demonstrates that the split-spectrum technique provides an effective correction. The split spectrum technique is also found to be superior to currently used approaches such as baseline fitting and multi-temporal averaging. The noise level is reduced by a factor of 70% in Greenland test areas and 90% in Antarctic test areas. @Article{liaoMeyerScheuchlMouginotJoughinRignotRSE2018IonosphericCorrectionInSAR, author = {Heming Liao and Franz J. Meyer and Bernd Scheuchl and Jeremie Mouginot and Ian Joughin and Eric Rignot}, title = {Ionospheric correction of InSAR data for accurate ice velocity measurement at polar regions}, journal = {Remote Sensing of Environment}, year = {2018}, volume = {209}, pages = {166-180}, issn = {0034-4257}, abstract = {Interferometric synthetic aperture radar (InSAR) has become an essential tool for measuring ice sheet velocity in the Polar Regions. At low radar frequencies, e.g. L-band (1.2 GHz) but also at higher frequency, e.g. C-band (5.6 GHz), the ionosphere has been documented to be an important source of noise in these data. In this paper, we employ a split-spectrum technique and investigate its performance for correcting ionospheric effects in InSAR-based ice velocity measurements in Greenland and Antarctica. Three case studies using ALOS PALSAR data are used to assess the performance of the split spectrum technique for ionosphere correction over a range of environmental parameters. We employ several approaches to evaluate the results, including visual inspection, profile analysis, comparison of experimental and theoretic errors, comparison with reference data from other sources, generation of double difference interferograms, and analysis of time series of multi-temporal data. Our experiments show that ionospheric distortions are observed regularly, and in our analyzed Greenland dataset and Antarctic dataset the ionospheric noise reaches 14 m/yr and 10 m/yr, respectively, which exceeds the signal associated with ice motion. Our analysis using several different approaches demonstrates that the split-spectrum technique provides an effective correction. The split spectrum technique is also found to be superior to currently used approaches such as baseline fitting and multi-temporal averaging. The noise level is reduced by a factor of 70% in Greenland test areas and 90% in Antarctic test areas.}, doi = {https://doi.org/10.1016/j.rse.2018.02.048}, file = {:liaoMeyerScheuchlMouginotJoughinRignotRSE2018IonosphericCorrectionInSAR.pdf:PDF}, keywords = {Synthetic aperture radar, SAR interferometry, Ice velocity, Range split spectrum, Data stacking, Ionosphere effect, Ionosphere correction}, owner = {ofrey}, url = {http://www.sciencedirect.com/science/article/pii/S0034425718300580}, } -
M. Lort,
A. Aguasca,
C. Lopez-Martinez,
and T. M. Marin.
Initial Evaluation of SAR Capabilities in UAV Multicopter Platforms.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
11(1):127-140,
January 2018.
Keyword(s): airborne radar,
geophysical image processing,
object detection,
radar polarimetry,
remote sensing by radar,
remotely operated vehicles,
synthetic aperture radar,
topography (Earth),
topographic mapping,
Universitat Politecnica de Catalunya,
AiR-based remote sensing,
Barcelona,
Spain,
UAV MP,
fully polarimetric SAR system,
airborne systems,
unmanned aerial vehicles,
object detection,
airborne synthetic aperture radar sensors,
UAV multicopter platform,
Synthetic aperture radar,
Unmanned aerial vehicles,
Apertures,
Remote sensing,
Sensor phenomena and characterization,
Trajectory,
Airborne synthetic aperture radar (SAR),
unmanned aerial vehicle (UAV) multicopter,
UAV SAR.
Abstract: Airborne synthetic aperture radar (SAR) sensors have been commonly used during the last decades to monitor different phenomena in medium-scale areas of observation, such as object detection and characterization or topographic mapping. The use of unmanned aerial vehicles (UAVs) is a cost-effective solution that offers higher operational flexibility than airborne systems to monitor these types of scenarios. The Universitat Politecnica de Catalunya has developed the first fully polarimetric SAR system at X-band integrated into a small UAV multicopter platform (UAV MP). The sensor, called AiR-based remote sensing, has been integrated into the platform overcoming restrictions of weight, space, robustness, and power consumption. To demonstrate the validity of the developed system, some measurement campaigns have been conducted in the outskirts of Barcelona, Spain. @Article{lortAguascaLopezMartinezMarinJSTARS2018SARCapabilitiesUAVMulticopter, author = {M. {Lort} and A. {Aguasca} and C. {Lopez-Martinez} and T. M. {Marin}}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, title = {Initial Evaluation of {SAR} Capabilities in {UAV} Multicopter Platforms}, year = {2018}, issn = {2151-1535}, month = jan, number = {1}, pages = {127-140}, volume = {11}, abstract = {Airborne synthetic aperture radar (SAR) sensors have been commonly used during the last decades to monitor different phenomena in medium-scale areas of observation, such as object detection and characterization or topographic mapping. The use of unmanned aerial vehicles (UAVs) is a cost-effective solution that offers higher operational flexibility than airborne systems to monitor these types of scenarios. The Universitat Politecnica de Catalunya has developed the first fully polarimetric SAR system at X-band integrated into a small UAV multicopter platform (UAV MP). The sensor, called AiR-based remote sensing, has been integrated into the platform overcoming restrictions of weight, space, robustness, and power consumption. To demonstrate the validity of the developed system, some measurement campaigns have been conducted in the outskirts of Barcelona, Spain.}, doi = {10.1109/JSTARS.2017.2752418}, file = {:lortAguascaLopezMartinezMarinJSTARS2018SARCapabilitiesUAVMulticopter.pdf:PDF}, keywords = {airborne radar;geophysical image processing;object detection;radar polarimetry;remote sensing by radar;remotely operated vehicles;synthetic aperture radar;topography (Earth);topographic mapping;Universitat Politecnica de Catalunya;AiR-based remote sensing;Barcelona;Spain;UAV MP;fully polarimetric SAR system;airborne systems;unmanned aerial vehicles;object detection;airborne synthetic aperture radar sensors;UAV multicopter platform;Synthetic aperture radar;Unmanned aerial vehicles;Apertures;Remote sensing;Sensor phenomena and characterization;Trajectory;Airborne synthetic aperture radar (SAR);unmanned aerial vehicle (UAV) multicopter;UAV SAR}, owner = {ofrey}, } -
Pooja Mahapatra,
Hans van der Marel,
Freek van Leijen,
Sami Samie Esfahany,
Roland Klees,
and Ramon Hanssen.
InSAR datum connection using GNSS-augmented radar transponders.
Journal of Geodesy,
92(1):21,
January 2018.
Abstract: Deformation estimates from Interferometric Synthetic Aperture Radar (InSAR) are relative: they form a`` free'' network referred to an arbitrary datum, e.g. by assuming a reference point in the image to be stable. However, some applications require ``absolute'' InSAR estimates, i.e. expressed in a well-defined terrestrial reference frame, e.g. to compare InSAR results with those of other techniques. We propose a methodology based on collocated InSAR and Global Navigation Satellite System (GNSS) measurements, achieved by rigidly attaching phase-stable millimetre-precision compact active radar transponders to GNSS antennas. We demonstrate this concept through a simulated example and practical case studies in the Netherlands. @Article{mahapatraVanDerMarelVanLeijenSamieiEsfahanyKleesHanssenJOG2018InSARandGNSSaugmentedTransponders, author = {Mahapatra, Pooja and van der Marel, Hans and van Leijen, Freek and Samie Esfahany, Sami and Klees, Roland and Hanssen, Ramon}, journal = {Journal of Geodesy}, title = {{InSAR} datum connection using {GNSS}-augmented radar transponders}, year = {2018}, issn = {1432-1394}, month = jan, number = {1}, pages = {21}, volume = {92}, abstract = {Deformation estimates from Interferometric Synthetic Aperture Radar (InSAR) are relative: they form a`` free'' network referred to an arbitrary datum, e.g. by assuming a reference point in the image to be stable. However, some applications require ``absolute'' InSAR estimates, i.e. expressed in a well-defined terrestrial reference frame, e.g. to compare InSAR results with those of other techniques. We propose a methodology based on collocated InSAR and Global Navigation Satellite System (GNSS) measurements, achieved by rigidly attaching phase-stable millimetre-precision compact active radar transponders to GNSS antennas. We demonstrate this concept through a simulated example and practical case studies in the Netherlands.}, date = {2018-01-01}, doi = {10.1007/s00190-017-1041-y}, file = {:mahapatraVanDerMarelVanLeijenSamieiEsfahanyKleesHanssenJOG2018InSARandGNSSaugmentedTransponders.pdf:PDF}, owner = {ofrey}, pdf = {../../../docs/mahapatraVanDerMarelVanLeijenSamieiEsfahanyKleesHanssenJOG2018InSARandGNSSaugmentedTransponders.pdf}, publisher = {Springer}, url = {http://dx.doi.org/10.1007/s00190-017-1041-y}, } -
Albert R. Monteith and Lars M. H. Ulander.
Temporal Survey of P- and L-Band Polarimetric Backscatter in Boreal Forests.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
11(10):3564-3577,
October 2018.
Keyword(s): SAR Tomography,
backscatter,
radar imaging,
radar polarimetry,
remote sensing by radar,
spaceborne radar,
synthetic aperture radar,
vegetation mapping,
temporal survey,
L-band polarimetric backscatter,
boreal forests,
environmental conditions,
seasonal variations,
backscattered radar signal,
biomass retrieval scheme,
synthetic aperture radar data,
electromagnetic scattering mechanisms,
biomass estimation algorithms,
L-band SAR missions,
temporal changes,
HV-polarized P,
L-band radar backscatter,
boreal forest site,
environmental parameters,
mature Norway spruce,
above-ground biomass,
approximately 250 tons/ha,
BorealScat tower-based scatterometer,
L-band backscatter,
HH/VV backscatter ratio,
average backscatter,
double-bounce scattering,
severe temporal decorrelation,
P-band temporal coherence,
mass 250.0 ton,
time 5.0 min,
noise figure 4.0 dB to 10.0 dB,
Synthetic aperture radar,
L-band,
Backscatter,
Biomass,
Antenna arrays,
Coherence,
Backscatter,
boreal forest,
L-band,
P-band,
synthetic aperture radar (SAR),
temporal coherence,
time series.
Abstract: Environmental conditions and seasonal variations affect the backscattered radar signal from a forest. This potentially causes errors in a biomass retrieval scheme using data from the synthetic aperture radar (SAR) data. A better understanding of these effects and the electromagnetic scattering mechanisms in forests is required to improve biomass estimation algorithms for current and upcoming P- and L-band SAR missions. In this paper, temporal changes in HH-, VV-, and HV-polarized P- and L-band radar backscatter and temporal coherence from a boreal forest site are analyzed in relation to environmental parameters. The radar data were collected from a stand of mature Norway spruce ( Picea abies (L.) Karst.) with an above-ground biomass of approximately 250 tons/ha at intervals of 5 min from January to August 2017 using the BorealScat tower-based scatterometer. It was observed that subzero temperatures during the winters cause large variations (4 to 10 dB) in P- and L-band backscatter, for which the HH/VV backscatter ratio offered some mitigation. High wind speeds were also seen to cause deviations in the average backscatter at P-band due to decreased double-bounce scattering. Severe temporal decorrelation was observed at L-band over timescales of days or more, whereas the P-band temporal coherence remained high (>0.9) for at least a month neglecting windy periods. Temporal coherence at P-band was highest during night times when wind speeds are low. @Article{monteithUlanderJSTARS2018TemporalPBandAndLBandPolarimetricBackscatter, author = {Monteith, Albert R. and Ulander, Lars M. H.}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, title = {Temporal Survey of {P-} and {L-}Band Polarimetric Backscatter in Boreal Forests}, year = {2018}, issn = {2151-1535}, month = oct, number = {10}, pages = {3564-3577}, volume = {11}, abstract = {Environmental conditions and seasonal variations affect the backscattered radar signal from a forest. This potentially causes errors in a biomass retrieval scheme using data from the synthetic aperture radar (SAR) data. A better understanding of these effects and the electromagnetic scattering mechanisms in forests is required to improve biomass estimation algorithms for current and upcoming P- and L-band SAR missions. In this paper, temporal changes in HH-, VV-, and HV-polarized P- and L-band radar backscatter and temporal coherence from a boreal forest site are analyzed in relation to environmental parameters. The radar data were collected from a stand of mature Norway spruce ( Picea abies (L.) Karst.) with an above-ground biomass of approximately 250 tons/ha at intervals of 5 min from January to August 2017 using the BorealScat tower-based scatterometer. It was observed that subzero temperatures during the winters cause large variations (4 to 10 dB) in P- and L-band backscatter, for which the HH/VV backscatter ratio offered some mitigation. High wind speeds were also seen to cause deviations in the average backscatter at P-band due to decreased double-bounce scattering. Severe temporal decorrelation was observed at L-band over timescales of days or more, whereas the P-band temporal coherence remained high (>0.9) for at least a month neglecting windy periods. Temporal coherence at P-band was highest during night times when wind speeds are low.}, doi = {10.1109/JSTARS.2018.2814825}, file = {:monteithUlanderJSTARS2018TemporalPBandAndLBandPolarimetricBackscatter.pdf:PDF}, keywords = {SAR Tomography, backscatter;radar imaging;radar polarimetry;remote sensing by radar;spaceborne radar;synthetic aperture radar;vegetation mapping;temporal survey;L-band polarimetric backscatter;boreal forests;environmental conditions;seasonal variations;backscattered radar signal;biomass retrieval scheme;synthetic aperture radar data;electromagnetic scattering mechanisms;biomass estimation algorithms;L-band SAR missions;temporal changes;HV-polarized P;L-band radar backscatter;boreal forest site;environmental parameters;mature Norway spruce;above-ground biomass;approximately 250 tons/ha;BorealScat tower-based scatterometer;L-band backscatter;HH/VV backscatter ratio;average backscatter;double-bounce scattering;severe temporal decorrelation;P-band temporal coherence;mass 250.0 ton;time 5.0 min;noise figure 4.0 dB to 10.0 dB;Synthetic aperture radar;L-band;Backscatter;Biomass;Antenna arrays;Coherence;Backscatter;boreal forest;L-band;P-band;synthetic aperture radar (SAR);temporal coherence;time series}, owner = {ofrey}, } -
Andrea Monti Guarnieri,
Antonio Leanza,
Andrea Recchia,
Stefano Tebaldini,
and Giovanna Venuti.
Atmospheric Phase Screen in GEO-SAR: Estimation and Compensation.
IEEE Transactions on Geoscience and Remote Sensing,
56(3):1668-1679,
2018.
Keyword(s): SAR Processing,
geosynchronous SAR,
Synthetic Aperture Radar,
Autofocus,
Atmospheric Modelling,
Apertures,
Atmospheric modeling,
Azimuth,
Delays,
Estimation,
Orbits,
Synthetic aperture radar,
Meteorology,
radar clutter,
radar imaging,
radar interferometry,
synthetic aperture radar (SAR).
Abstract: We study the impact of atmospheric turbulence, specifically the wet tropospheric delay, in that synthetic aperture radar (SAR) with very long integration time, from minutes to hours, and wide swaths, such as the geosynchronous or geostationary SAR. In such systems, the atmospheric phase screen (APS) cannot be assumed frozen in time as for Low Earth Orbit or airborne SARs nor constant in space as for the ground-based SAR. The impact of space-time turbulence on SAR focusing is quantitatively assessed, and a novel focusing method that integrates APS estimation and compensation is proposed. Performances are evaluated as a function of SAR parameters, mainly the wavelength, based on a parametric model of the APS variogram, and results achieved by a simulating realistic scenario are shown. @Article{montiGuarnieriLeanzaRecchiaTebaldiniVenutiTGRS2018APSinGEOSAREstimationCompensation, author = {Monti Guarnieri, Andrea and Leanza, Antonio and Recchia, Andrea and Tebaldini, Stefano and Venuti,Giovanna}, title = {Atmospheric Phase Screen in {GEO-SAR}: Estimation and Compensation}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, year = {2018}, volume = {56}, number = {3}, pages = {1668-1679}, issn = {0196-2892}, abstract = {We study the impact of atmospheric turbulence, specifically the wet tropospheric delay, in that synthetic aperture radar (SAR) with very long integration time, from minutes to hours, and wide swaths, such as the geosynchronous or geostationary SAR. In such systems, the atmospheric phase screen (APS) cannot be assumed frozen in time as for Low Earth Orbit or airborne SARs nor constant in space as for the ground-based SAR. The impact of space-time turbulence on SAR focusing is quantitatively assessed, and a novel focusing method that integrates APS estimation and compensation is proposed. Performances are evaluated as a function of SAR parameters, mainly the wavelength, based on a parametric model of the APS variogram, and results achieved by a simulating realistic scenario are shown.}, doi = {10.1109/TGRS.2017.2766084}, file = {:montiGuarnieriLeanzaRecchiaTebaldiniVenutiTGRS2018APSinGEOSAREstimationCompensation.pdf:PDF}, keywords = {SAR Processing, geosynchronous SAR, Synthetic Aperture Radar, Autofocus, Atmospheric Modelling, Apertures;Atmospheric modeling;Azimuth;Delays;Estimation;Orbits;Synthetic aperture radar;Meteorology;radar clutter;radar imaging;radar interferometry;synthetic aperture radar (SAR)}, owner = {ofrey}, pdf = {../../../docs/montiGuarnieriLeanzaRecchiaTebaldiniVenutiTGRS2018APSinGEOSAREstimationCompensation.pdf}, } -
Andrea Virgilio Monti-Guarnieri,
Maria Antonia Brovelli,
Marco Manzoni,
Mauro Mariotti d'Alessandro,
Monia Elisa Molinari,
and Daniele Oxoli.
Coherent Change Detection for Multipass SAR.
IEEE Transactions on Geoscience and Remote Sensing,
56(11):6811-6822,
November 2018.
Keyword(s): SAR Processing,
Coherent Change Detection,
CCD.
Abstract: This paper focuses on the detection, from a stack of repeated-pass interferometric synthetic aperture radar (SAR) images, of such changes causing a target to completely lose the correlation between one epoch and another. This can be the consequence of human activities, such as construction, destruction, and agricultural activities, and also be the consequence of hazards, such as earthquake, landslides, or flooding, to buildings or terrains. The millimetric sensitivity of SAR makes it valuable for detecting such changes. This paper approaches two coherent change detection methods: a space coherent, time incoherent one and a full space and time coherent one, both based on the generalized likelihood ratiob (LR) test. A preliminary validation of the method is provided by processing two Sentinel-1 data stacks of 2016 Central Italy earthquake and by comparing the results with the map of damaged buildings in Amatrice and Accumoli made by Copernicus Emergency Management Service. @Article{montiGuarnieriEtAlTGARS2018CoherentChangeDetectionForMultipassSAR, author = {Monti-Guarnieri, Andrea Virgilio and Brovelli, Maria Antonia and Manzoni, Marco and Mariotti d'Alessandro, Mauro and Molinari, Monia Elisa and Oxoli, Daniele}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, title = {Coherent Change Detection for Multipass {SAR}}, year = {2018}, issn = {1558-0644}, month = {Nov}, number = {11}, pages = {6811-6822}, volume = {56}, abstract = {This paper focuses on the detection, from a stack of repeated-pass interferometric synthetic aperture radar (SAR) images, of such changes causing a target to completely lose the correlation between one epoch and another. This can be the consequence of human activities, such as construction, destruction, and agricultural activities, and also be the consequence of hazards, such as earthquake, landslides, or flooding, to buildings or terrains. The millimetric sensitivity of SAR makes it valuable for detecting such changes. This paper approaches two coherent change detection methods: a space coherent, time incoherent one and a full space and time coherent one, both based on the generalized likelihood ratiob (LR) test. A preliminary validation of the method is provided by processing two Sentinel-1 data stacks of 2016 Central Italy earthquake and by comparing the results with the map of damaged buildings in Amatrice and Accumoli made by Copernicus Emergency Management Service.}, doi = {10.1109/TGRS.2018.2843560}, file = {:montiGuarnieriEtAlTGARS2018CoherentChangeDetectionForMultipassSAR.pdf:PDF}, keywords = {SAR Processing, Coherent Change Detection, CCD}, owner = {ofrey}, } -
A. G. Mullissa,
D. Perissin,
V. A. Tolpekin,
and A. Stein.
Polarimetry-Based Distributed Scatterer Processing Method for PSI Applications.
IEEE Trans. Geosci. Remote Sens.,
PP(99):1-12,
2018.
Keyword(s): Coherence,
Interferometry,
Matrix decomposition,
Optimization,
Synthetic aperture radar,
Adaptive filtering,
distributed scatterers (DSs),
multitemporal interferometric synthetic aperture radar (InSAR),
permanent scatterer interferometry (PSI),
polarimetric optimization,
polarimetric synthetic aperture radar interferometry..
Abstract: Permanent scatterer interferometry is a multitemporal interferometric synthetic aperture radar technique that produces high-accuracy ground deformation measurement. A high density of permanent scatterer (PS) is required to provide accurate results. In natural environments with low PS density, distributed scatterers (DSs) could serve as additional coherent observations. This paper introduces a polarimetric scattering property-based adaptive filtering method that preserves PS candidates and filters DS candidates. To further increase the coherence estimate of DS candidates, the technique includes a complex coherence decomposition that adaptively selects the most stable scattering mechanisms, thus improving pixel coherence estimation. The proposed method was evaluated on 11 quad-polarized ALOS PALSAR images and 21 dual-polarized Sentinel-1 images acquired over San Fernando Valley, CA, USA, and Groningen, The Netherlands, respectively. The application of this method increased the number of coherent pixels by almost a factor of eight compared with a single-polarization channel. This paper concludes that a coherence estimate can be significantly improved by applying scattering property-based adaptive filtering and coherence matrix decomposition and accurate displacement measurements can be achieved. @Article{mullissaPerissinTolpekinSteinTGRS2018PolarimetryBasedDistributedScatterersForPSI, author = {A. G. Mullissa and D. Perissin and V. A. Tolpekin and A. Stein}, title = {Polarimetry-Based Distributed Scatterer Processing Method for {PSI} Applications}, journal = {IEEE Trans. Geosci. Remote Sens.}, year = {2018}, volume = {PP}, number = {99}, pages = {1-12}, issn = {0196-2892}, abstract = {Permanent scatterer interferometry is a multitemporal interferometric synthetic aperture radar technique that produces high-accuracy ground deformation measurement. A high density of permanent scatterer (PS) is required to provide accurate results. In natural environments with low PS density, distributed scatterers (DSs) could serve as additional coherent observations. This paper introduces a polarimetric scattering property-based adaptive filtering method that preserves PS candidates and filters DS candidates. To further increase the coherence estimate of DS candidates, the technique includes a complex coherence decomposition that adaptively selects the most stable scattering mechanisms, thus improving pixel coherence estimation. The proposed method was evaluated on 11 quad-polarized ALOS PALSAR images and 21 dual-polarized Sentinel-1 images acquired over San Fernando Valley, CA, USA, and Groningen, The Netherlands, respectively. The application of this method increased the number of coherent pixels by almost a factor of eight compared with a single-polarization channel. This paper concludes that a coherence estimate can be significantly improved by applying scattering property-based adaptive filtering and coherence matrix decomposition and accurate displacement measurements can be achieved.}, doi = {10.1109/TGRS.2018.2798705}, keywords = {Coherence;Interferometry;Matrix decomposition;Optimization;Synthetic aperture radar;Adaptive filtering;distributed scatterers (DSs);multitemporal interferometric synthetic aperture radar (InSAR);permanent scatterer interferometry (PSI);polarimetric optimization;polarimetric synthetic aperture radar interferometry.}, owner = {ofrey}, } -
Elvira Musico,
Claudio Cesaroni,
Luca Spogli,
John P. Merryman Boncori,
De Franceschi Giorgiana,
and Roberto Seu.
The Total Electron Content From InSAR and GNSS: A Midlatitude Study.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
11(5):1725-1733,
May 2018.
Keyword(s): SAR Processing,
Ionosphere,
Global Positioning System,
atmospheric techniques,
radar interferometry,
rain,
remote sensing by radar,
satellite navigation,
synthetic aperture radar,
ALOS-PALSAR,
GNSS experimental measurements,
GNSS receivers,
InSAR images,
L-band InSAR,
RING network,
Rete Integrata Nazionale GPS network,
TEC variability,
advanced land observing satellite,
array type L-band synthetic aperture radar,
correlation coefficient,
dense network,
global navigation satellite system receivers,
interferometric phase,
interferometric synthetic aperture radar,
ionospheric information,
midlatitude study,
night-time case studies,
reference true ionospheric TEC,
total electron content,
tropospheric contribution,
Azimuth,
Correlation,
Earth,
Global navigation satellite system,
Ionosphere,
Receivers,
Synthetic aperture radar,
Global positioning system,
ionosphere,
synthetic aperture radar (SAR).
Abstract: The total electron content (TEC) measured from the interferometric synthetic aperture radar (InSAR) and from a dense network of global navigation satellite system (GNSS) receivers are used to assess the capability of InSAR to retrieve ionospheric information, when the tropospheric contribution to the interferometric phase is reasonably negligible. With this aim, we select three night-time case studies over Italy and investigate the correlation between TEC from advanced land observing satellite-phased array type L-band synthetic aperture radar (ALOS-PALSAR) and from the Rete Integrata Nazionale GPS (RING) network, the latter considered as the reference true ionospheric TEC. To retrieve the TEC variability from ALOS-PALSAR, we first investigate the correlation between the integral of the azimuth shifts and the interferometric phase in the absence of ground motions (e.g., earthquakes) and/or heavy rain events. If correlation exists (as in two out of three case studies under investigation), we can assume the tropospheric contribution to the interferometric phase as negligible and the TEC variability from L-band InSAR can be retrieved. For these two case studies, the comparison between the TEC from the InSAR images and from the RING network is quite encouraging as the correlation coefficient is R ~ 0.67 in the first case and R ~ 0.83 in the second case. This result highlights the potential to combine InSAR and GNSS experimental measurements to investigate small-scale spatial variability of TEC, in particular over regions scarcely covered by ground-based GNSS receivers. @Article{musicoCesaroniSpogliMerrymanDeFranceschiSeuJSTARS2018IonoTECInSARandGNSS, author = {Musico, Elvira and Cesaroni, Claudio and Spogli, Luca and Merryman Boncori, John P. and De Franceschi Giorgiana and Seu,Roberto}, title = {The Total Electron Content From {InSAR} and {GNSS}: A Midlatitude Study}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, year = {2018}, volume = {11}, number = {5}, pages = {1725-1733}, month = {May}, issn = {1939-1404}, abstract = {The total electron content (TEC) measured from the interferometric synthetic aperture radar (InSAR) and from a dense network of global navigation satellite system (GNSS) receivers are used to assess the capability of InSAR to retrieve ionospheric information, when the tropospheric contribution to the interferometric phase is reasonably negligible. With this aim, we select three night-time case studies over Italy and investigate the correlation between TEC from advanced land observing satellite-phased array type L-band synthetic aperture radar (ALOS-PALSAR) and from the Rete Integrata Nazionale GPS (RING) network, the latter considered as the reference true ionospheric TEC. To retrieve the TEC variability from ALOS-PALSAR, we first investigate the correlation between the integral of the azimuth shifts and the interferometric phase in the absence of ground motions (e.g., earthquakes) and/or heavy rain events. If correlation exists (as in two out of three case studies under investigation), we can assume the tropospheric contribution to the interferometric phase as negligible and the TEC variability from L-band InSAR can be retrieved. For these two case studies, the comparison between the TEC from the InSAR images and from the RING network is quite encouraging as the correlation coefficient is R ~ 0.67 in the first case and R ~ 0.83 in the second case. This result highlights the potential to combine InSAR and GNSS experimental measurements to investigate small-scale spatial variability of TEC, in particular over regions scarcely covered by ground-based GNSS receivers.}, doi = {10.1109/JSTARS.2018.2812305}, file = {:musicoCesaroniSpogliMerrymanDeFranceschiSeuJSTARS2018IonoTECInSARandGNSS.pdf:PDF}, keywords = {SAR Processing, Ionosphere, Global Positioning System;atmospheric techniques;radar interferometry;rain;remote sensing by radar;satellite navigation;synthetic aperture radar;ALOS-PALSAR;GNSS experimental measurements;GNSS receivers;InSAR images;L-band InSAR;RING network;Rete Integrata Nazionale GPS network;TEC variability;advanced land observing satellite;array type L-band synthetic aperture radar;correlation coefficient;dense network;global navigation satellite system receivers;interferometric phase;interferometric synthetic aperture radar;ionospheric information;midlatitude study;night-time case studies;reference true ionospheric TEC;total electron content;tropospheric contribution;Azimuth;Correlation;Earth;Global navigation satellite system;Ionosphere;Receivers;Synthetic aperture radar;Global positioning system;ionosphere;synthetic aperture radar (SAR)}, owner = {ofrey}, } -
NI.
The Total Electron Content From InSAR and GNSS: A Midlatitude Study.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
11(5):1725-1733,
May 2018.
Keyword(s): SAR Processing,
Ionosphere,
Global Positioning System,
atmospheric techniques,
radar interferometry,
rain,
remote sensing by radar,
satellite navigation,
synthetic aperture radar,
ALOS-PALSAR,
GNSS experimental measurements,
GNSS receivers,
InSAR images,
L-band InSAR,
RING network,
Rete Integrata Nazionale GPS network,
TEC variability,
advanced land observing satellite,
array type L-band synthetic aperture radar,
correlation coefficient,
dense network,
global navigation satellite system receivers,
interferometric phase,
interferometric synthetic aperture radar,
ionospheric information,
midlatitude study,
night-time case studies,
reference true ionospheric TEC,
total electron content,
tropospheric contribution,
Azimuth,
Correlation,
Earth,
Global navigation satellite system,
Ionosphere,
Receivers,
Synthetic aperture radar,
Global positioning system,
ionosphere,
synthetic aperture radar (SAR).
Abstract: The total electron content (TEC) measured from the interferometric synthetic aperture radar (InSAR) and from a dense network of global navigation satellite system (GNSS) receivers are used to assess the capability of InSAR to retrieve ionospheric information, when the tropospheric contribution to the interferometric phase is reasonably negligible. With this aim, we select three night-time case studies over Italy and investigate the correlation between TEC from advanced land observing satellite-phased array type L-band synthetic aperture radar (ALOS-PALSAR) and from the Rete Integrata Nazionale GPS (RING) network, the latter considered as the reference true ionospheric TEC. To retrieve the TEC variability from ALOS-PALSAR, we first investigate the correlation between the integral of the azimuth shifts and the interferometric phase in the absence of ground motions (e.g., earthquakes) and/or heavy rain events. If correlation exists (as in two out of three case studies under investigation), we can assume the tropospheric contribution to the interferometric phase as negligible and the TEC variability from L-band InSAR can be retrieved. For these two case studies, the comparison between the TEC from the InSAR images and from the RING network is quite encouraging as the correlation coefficient is R ~ 0.67 in the first case and R ~ 0.83 in the second case. This result highlights the potential to combine InSAR and GNSS experimental measurements to investigate small-scale spatial variability of TEC, in particular over regions scarcely covered by ground-based GNSS receivers. @Article{musicoCesaroniSpogliMerrymanDeFranceschiSeuJSTARS2018IonoTECInSARandGNSS, author = {NI}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, title = {The Total Electron Content From {InSAR} and {GNSS}: A Midlatitude Study}, year = {2018}, issn = {1939-1404}, month = {May}, number = {5}, pages = {1725-1733}, volume = {11}, abstract = {The total electron content (TEC) measured from the interferometric synthetic aperture radar (InSAR) and from a dense network of global navigation satellite system (GNSS) receivers are used to assess the capability of InSAR to retrieve ionospheric information, when the tropospheric contribution to the interferometric phase is reasonably negligible. With this aim, we select three night-time case studies over Italy and investigate the correlation between TEC from advanced land observing satellite-phased array type L-band synthetic aperture radar (ALOS-PALSAR) and from the Rete Integrata Nazionale GPS (RING) network, the latter considered as the reference true ionospheric TEC. To retrieve the TEC variability from ALOS-PALSAR, we first investigate the correlation between the integral of the azimuth shifts and the interferometric phase in the absence of ground motions (e.g., earthquakes) and/or heavy rain events. If correlation exists (as in two out of three case studies under investigation), we can assume the tropospheric contribution to the interferometric phase as negligible and the TEC variability from L-band InSAR can be retrieved. For these two case studies, the comparison between the TEC from the InSAR images and from the RING network is quite encouraging as the correlation coefficient is R ~ 0.67 in the first case and R ~ 0.83 in the second case. This result highlights the potential to combine InSAR and GNSS experimental measurements to investigate small-scale spatial variability of TEC, in particular over regions scarcely covered by ground-based GNSS receivers.}, doi = {10.1109/JSTARS.2018.2812305}, file = {:musicoCesaroniSpogliMerrymanDeFranceschiSeuJSTARS2018IonoTECInSARandGNSS.pdf:PDF}, keywords = {SAR Processing, Ionosphere, Global Positioning System;atmospheric techniques;radar interferometry;rain;remote sensing by radar;satellite navigation;synthetic aperture radar;ALOS-PALSAR;GNSS experimental measurements;GNSS receivers;InSAR images;L-band InSAR;RING network;Rete Integrata Nazionale GPS network;TEC variability;advanced land observing satellite;array type L-band synthetic aperture radar;correlation coefficient;dense network;global navigation satellite system receivers;interferometric phase;interferometric synthetic aperture radar;ionospheric information;midlatitude study;night-time case studies;reference true ionospheric TEC;total electron content;tropospheric contribution;Azimuth;Correlation;Earth;Global navigation satellite system;Ionosphere;Receivers;Synthetic aperture radar;Global positioning system;ionosphere;synthetic aperture radar (SAR)}, owner = {ofrey}, } -
Stephan Palm,
Rainer Sommer,
and Uwe Stilla.
Mobile Radar Mapping --- Subcentimeter SAR Imaging of Roads.
IEEE Transactions on Geoscience and Remote Sensing,
56(11):6734-6746,
November 2018.
Keyword(s): SAR Processing,
Azimuth Focusing,
FMCW,
Back Projection,
Time-Domain Back-Projection,
TDBP,
FFBP,
Fast-Factorized Back-Projection,
CW radar,
digital elevation models,
FM radar,
geophysical image processing,
Global Positioning System,
image reconstruction,
image resolution,
radar imaging,
remote sensing by radar,
synthetic aperture radar,
mobile radar mapping-subcentimeter SAR imaging,
ultrahigh-resolution synthetic aperture radar data,
related theoretical background,
imaging method,
backprojection techniques,
potential errors,
correct geometry,
imaging quality,
point target simulations,
suitable digital elevation model,
illuminated scene,
conventional roads,
mobile mapping scenarios,
SAR images,
output data,
reference targets,
GPS-INS data,
conventional 3-D Point Cloud Software,
geometric distortions,
subcentimeter SAR imaging,
active frequency-modulated continuous wave radar system,
frequency 300.0 GHz,
Synthetic aperture radar,
Sensors,
Radar imaging,
Roads,
Laser radar,
Geometry,
Millimeter wave radar,
radar resolution,
radar signal processing,
road vehicle radar.
Abstract: In this paper, we present a strategy for focusing ultrahigh-resolution synthetic aperture radar (SAR) data for mobile radar mapping. We illustrate the related theoretical background and required extensions on the imaging method based on backprojection techniques. The influence of potential errors in estimating a correct geometry with respect to the imaging quality is investigated in detail by point target simulations. As backprojection techniques require precise knowledge of the topography in close range, the new strategy instantly uses the GPS/INS data of the trajectory to define a suitable digital elevation model of the illuminated scene. We have tested the strategy by driving on conventional roads with an active frequency-modulated continuous wave radar system operating at 300 GHz. Different reference targets were placed in the scene, and the accuracy of the method was evaluated. The results experimentally reveal that the lower terahertz band is capable of subcentimeter SAR imaging in mobile mapping scenarios at very high quality. We have shown that narrow cracks in the asphalt of roads can be detected and fine-scale objects on millimeter size can be displayed. Geometric distortions in the SAR images are significantly reduced allowing the measurements of infrastructure. The output data can at last be transferred to the conventional 3-D Point Cloud Software for further processing. @Article{palmSommerStillaTGRS2018MobileRadarMappingSubCentimeterImaging, author = {Stephan Palm and Rainer Sommer and Uwe Stilla}, title = {Mobile Radar Mapping --- Subcentimeter {SAR} Imaging of Roads}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, year = {2018}, volume = {56}, number = {11}, pages = {6734-6746}, month = {Nov}, issn = {0196-2892}, abstract = {In this paper, we present a strategy for focusing ultrahigh-resolution synthetic aperture radar (SAR) data for mobile radar mapping. We illustrate the related theoretical background and required extensions on the imaging method based on backprojection techniques. The influence of potential errors in estimating a correct geometry with respect to the imaging quality is investigated in detail by point target simulations. As backprojection techniques require precise knowledge of the topography in close range, the new strategy instantly uses the GPS/INS data of the trajectory to define a suitable digital elevation model of the illuminated scene. We have tested the strategy by driving on conventional roads with an active frequency-modulated continuous wave radar system operating at 300 GHz. Different reference targets were placed in the scene, and the accuracy of the method was evaluated. The results experimentally reveal that the lower terahertz band is capable of subcentimeter SAR imaging in mobile mapping scenarios at very high quality. We have shown that narrow cracks in the asphalt of roads can be detected and fine-scale objects on millimeter size can be displayed. Geometric distortions in the SAR images are significantly reduced allowing the measurements of infrastructure. The output data can at last be transferred to the conventional 3-D Point Cloud Software for further processing.}, doi = {10.1109/TGRS.2018.2842643}, file = {:palmSommerStillaTGRS2018MobileRadarMappingSubCentimeterImaging.pdf:PDF}, keywords = {SAR Processing, Azimuth Focusing, FMCW, Back Projection, Time-Domain Back-Projection, TDBP, FFBP, Fast-Factorized Back-Projection, CW radar;digital elevation models;FM radar;geophysical image processing;Global Positioning System;image reconstruction;image resolution;radar imaging;remote sensing by radar;synthetic aperture radar;mobile radar mapping-subcentimeter SAR imaging;ultrahigh-resolution synthetic aperture radar data;related theoretical background;imaging method;backprojection techniques;potential errors;correct geometry;imaging quality;point target simulations;suitable digital elevation model;illuminated scene;conventional roads;mobile mapping scenarios;SAR images;output data;reference targets;GPS-INS data;conventional 3-D Point Cloud Software;geometric distortions;subcentimeter SAR imaging;active frequency-modulated continuous wave radar system;frequency 300.0 GHz;Synthetic aperture radar;Sensors;Radar imaging;Roads;Laser radar;Geometry;Millimeter wave radar;radar resolution;radar signal processing;road vehicle radar;synthetic aperture radar (SAR)}, owner = {ofrey}, } -
Matteo Pardini,
Marivi Tello,
Victor Cazcarra-Bes,
K. P. Papathanassiou,
and I. Hajnsek.
L- and P-Band 3-D SAR Reflectivity Profiles Versus Lidar Waveforms: The AfriSAR Case.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
11(10):3386-3401,
October 2018.
Keyword(s): SAR Processing,
SAR Tomography,
airborne radar,
backscatter,
forestry,
geophysical techniques,
optical radar,
radar imaging,
radar polarimetry,
remote sensing by laser beam,
remote sensing by radar,
synthetic aperture radar,
vegetation,
vegetation mapping,
NASA Land,
Ice Sensor lidar datasets,
AfriSAR campaign,
LVIS data,
plot field measurements,
ground-to-volume power ratio,
physical forest structure descriptors,
vertical structure indices,
3-D radar reflectivity,
LVIS profiles,
P-band 3-D,
AfriSAR case,
P-band vertical backscattering profiles,
synthetic aperture radar tomography,
light detection,
DLR F-SAR,
tropical forest structure types,
Forestry,
Synthetic aperture radar,
Laser radar,
Radar tracking,
L-band,
Vegetation,
Forest structure,
full waveforms,
light detection and ranging (lidar),
SAR tomography (TomoSAR),
synthetic aperture radar (SAR),
tropical forest.
Abstract: The aim of this paper is to compare L- and P-band vertical backscattering profiles estimated by means of synthetic aperture radar (SAR) tomography and full light detection and ranging (lidar) waveforms in terms of their ability to distinguish different tropical forest structure types. The comparison relies on the unique DLR F-SAR and NASA Land, Vegetation and Ice Sensor (LVIS) lidar datasets acquired in 2016 in the frame of the AfriSAR campaign. In particular, F-SAR and LVIS data over three different test sites complemented by plot field measurements are used. First, the SAR and lidar three-dimensional (3-D) datasets are compared and discussed on a qualitative basis. The ability to penetrate into and through the canopy down to the ground is assessed at L- and P-band in terms of both the ground-to-volume power ratio and the performance to estimate the location of the underlying ground. The effect of polarimetry on the visibility of the ground is discussed as well. Finally, the 3-D measurements for each configuration are compared with respect to their ability to derive physical forest structure descriptors. For this, vertical structure indices derived from the volume-only 3-D radar reflectivity at L- and P-band and from the LVIS profiles are compared against each other as well as against plot-derived indices. @Article{pardiniTelloCazcarraBesPapathanassiouHajnsek2018LBandAndPBandSARTomoAgainstLiDARAfriSAR, author = {Pardini, Matteo and Tello, Marivi and Cazcarra-Bes, Victor and Papathanassiou, K. P. and Hajnsek, I.}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, title = {{L-} and {P-Band} {3-D} {SAR} Reflectivity Profiles Versus {Lidar} Waveforms: The {AfriSAR} Case}, year = {2018}, month = {Oct}, number = {10}, pages = {3386-3401}, volume = {11}, abstract = {The aim of this paper is to compare L- and P-band vertical backscattering profiles estimated by means of synthetic aperture radar (SAR) tomography and full light detection and ranging (lidar) waveforms in terms of their ability to distinguish different tropical forest structure types. The comparison relies on the unique DLR F-SAR and NASA Land, Vegetation and Ice Sensor (LVIS) lidar datasets acquired in 2016 in the frame of the AfriSAR campaign. In particular, F-SAR and LVIS data over three different test sites complemented by plot field measurements are used. First, the SAR and lidar three-dimensional (3-D) datasets are compared and discussed on a qualitative basis. The ability to penetrate into and through the canopy down to the ground is assessed at L- and P-band in terms of both the ground-to-volume power ratio and the performance to estimate the location of the underlying ground. The effect of polarimetry on the visibility of the ground is discussed as well. Finally, the 3-D measurements for each configuration are compared with respect to their ability to derive physical forest structure descriptors. For this, vertical structure indices derived from the volume-only 3-D radar reflectivity at L- and P-band and from the LVIS profiles are compared against each other as well as against plot-derived indices.}, doi = {10.1109/JSTARS.2018.2847033}, file = {:pardiniTelloCazcarraBesPapathanassiouHajnsek2018LBandAndPBandSARTomoAgainstLiDARAfriSAR.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, airborne radar;backscatter;forestry;geophysical techniques;optical radar;radar imaging;radar polarimetry;remote sensing by laser beam;remote sensing by radar;synthetic aperture radar;vegetation;vegetation mapping;NASA Land;Ice Sensor lidar datasets;AfriSAR campaign;LVIS data;plot field measurements;ground-to-volume power ratio;physical forest structure descriptors;vertical structure indices;3-D radar reflectivity;LVIS profiles;P-band 3-D;AfriSAR case;P-band vertical backscattering profiles;synthetic aperture radar tomography;light detection;DLR F-SAR;tropical forest structure types;Forestry;Synthetic aperture radar;Laser radar;Radar tracking;L-band;Vegetation;Forest structure;full waveforms;light detection and ranging (lidar);SAR tomography (TomoSAR);synthetic aperture radar (SAR);tropical forest}, owner = {ofrey}, } -
Antonio Pauciullo,
Diego Reale,
Walter Franzé,
and Gianfranco Fornaro.
Multi-Look in GLRT-Based Detection of Single and Double Persistent Scatterers.
IEEE Trans. Geosci. Remote Sens.,
56(9):5125-5137,
September 2018.
Keyword(s): SAR Processing,
SAR Tomography,
Multi-look,
Coherence,
Detectors,
Interferometry,
Spatial resolution,
Synthetic aperture radar,
Tomography,
Detection,
SAR tomography,
generalized likelihood ratio test,
multi-look,
persistent scatterers (PSs).
Abstract: Persistent scatterer (PS) interferometry and more recently synthetic aperture radar tomography have shown to be powerful tools in urban scenarios for providing 3-D point clouds in the reconstruction of buildings as well as in the monitoring of their possible slow temporal deformations. The detection of PSs represents a fundamental aspect, which in the literature has been mainly addressed at full resolution (single-look detection), thus considering only the scatterer coherence properties along the different acquisitions. In this paper, we investigate the benefits offered by the usage of multiple observation looks. Multi-look generalized likelihood ratio test detection schemes are derived and analyzed in terms of detection performances. The analysis shows that even a slight multi-look can provide a dramatic improvement on the detection capability both on simulated and real data, especially in the areas characterized by a low signal-to-noise ratio and in the presence of a limited number of acquisitions. @Article{pauciulloRealeFranzeFornaroTGRS2018MultiLookGLRTPSITomo, author = {Antonio Pauciullo and Diego Reale and Walter Franz{\'e} and Gianfranco Fornaro}, title = {Multi-Look in {GLRT}-Based Detection of Single and Double Persistent Scatterers}, journal = {IEEE Trans. Geosci. Remote Sens.}, year = {2018}, volume = {56}, number = {9}, pages = {5125-5137}, month = sep, issn = {0196-2892}, abstract = {Persistent scatterer (PS) interferometry and more recently synthetic aperture radar tomography have shown to be powerful tools in urban scenarios for providing 3-D point clouds in the reconstruction of buildings as well as in the monitoring of their possible slow temporal deformations. The detection of PSs represents a fundamental aspect, which in the literature has been mainly addressed at full resolution (single-look detection), thus considering only the scatterer coherence properties along the different acquisitions. In this paper, we investigate the benefits offered by the usage of multiple observation looks. Multi-look generalized likelihood ratio test detection schemes are derived and analyzed in terms of detection performances. The analysis shows that even a slight multi-look can provide a dramatic improvement on the detection capability both on simulated and real data, especially in the areas characterized by a low signal-to-noise ratio and in the presence of a limited number of acquisitions.}, doi = {10.1109/TGRS.2018.2809538}, keywords = {SAR Processing, SAR Tomography, Multi-look, Coherence;Detectors;Interferometry;Spatial resolution;Synthetic aperture radar;Tomography;Detection;SAR tomography;generalized likelihood ratio test;multi-look;persistent scatterers (PSs)}, owner = {ofrey}, } -
Muriel Pinheiro,
Andreas Reigber,
Rolf Scheiber,
Pau Prats-Iraola,
and Alberto Moreira.
Generation of Highly Accurate DEMs Over Flat Areas by Means of Dual-Frequency and Dual-Baseline Airborne SAR Interferometry.
IEEE Transactions on Geoscience and Remote Sensing,
pp 1-30,
2018.
Keyword(s): Calibration,
Data models,
Decorrelation,
Interferometry,
Standards,
Surfaces,
Synthetic aperture radar,
Digital elevation model (DEM),
SAR interferometry (InSAR).,
dual frequency,
repeat-pass interferometry.
Abstract: In this paper, a dual-frequency and dual-baseline (DFDB) processing framework for the extraction of high-precision terrain information from airborne interferometric synthetic aperture radar (SAR) data is presented. Specifically, we propose the use of two single-pass data sets acquired simultaneously in two different frequency bands and two large-baseline repeat-pass data sets also acquired simultaneously in two frequency bands. The configuration profits from the stability of the single-pass derived elevation maps in relation to spatially correlated artifacts as well as from the increased sensitivity associated with large-baseline acquisitions. Moreover, the dual-frequency nature of the data set enables the tackling of the phase unwrapping issue, promoting the retrieval of unambiguous measurements. Several algorithms for the interferometric processing of the DFDB airborne data set are proposed, including the outline of multichannel phase calibration and unwrapping error correction strategies and approaches to remove spatially correlated artifacts and extract the common underlying topography. Elevation models generated from a DFDB data set acquired with the airborne F-SAR sensor over tidal flats in northern Germany are presented, and comparisons with an airborne laser scanner reference show errors with a standard deviation of around 14 cm and a mean absolute deviation of less than 10 cm. @Article{pinheiroReigberScheiberPratsMoreiraTGRS2018HighlyAccurateDEMsWithDualFreqDualBaselineAirborneInSAR, author = {Muriel Pinheiro and Andreas Reigber and Rolf Scheiber and Pau Prats-Iraola and Alberto Moreira}, title = {Generation of Highly Accurate DEMs Over Flat Areas by Means of Dual-Frequency and Dual-Baseline Airborne SAR Interferometry}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, year = {2018}, pages = {1-30}, issn = {0196-2892}, abstract = {In this paper, a dual-frequency and dual-baseline (DFDB) processing framework for the extraction of high-precision terrain information from airborne interferometric synthetic aperture radar (SAR) data is presented. Specifically, we propose the use of two single-pass data sets acquired simultaneously in two different frequency bands and two large-baseline repeat-pass data sets also acquired simultaneously in two frequency bands. The configuration profits from the stability of the single-pass derived elevation maps in relation to spatially correlated artifacts as well as from the increased sensitivity associated with large-baseline acquisitions. Moreover, the dual-frequency nature of the data set enables the tackling of the phase unwrapping issue, promoting the retrieval of unambiguous measurements. Several algorithms for the interferometric processing of the DFDB airborne data set are proposed, including the outline of multichannel phase calibration and unwrapping error correction strategies and approaches to remove spatially correlated artifacts and extract the common underlying topography. Elevation models generated from a DFDB data set acquired with the airborne F-SAR sensor over tidal flats in northern Germany are presented, and comparisons with an airborne laser scanner reference show errors with a standard deviation of around 14 cm and a mean absolute deviation of less than 10 cm.}, doi = {10.1109/TGRS.2018.2817122}, file = {:pinheiroReigberScheiberPratsMoreiraTGRS2018HighlyAccurateDEMsWithDualFreqDualBaselineAirborneInSAR.pdf:PDF}, keywords = {Calibration;Data models;Decorrelation;Interferometry;Standards;Surfaces;Synthetic aperture radar;Digital elevation model (DEM);SAR interferometry (InSAR).;dual frequency;repeat-pass interferometry}, } -
Pau Prats-Iraola,
Paco Lopez-Dekker,
Francesco De Zan,
Nestor Yague-Martinez,
Mariantonietta Zonno,
and Marc Rodriguez-Cassola.
Performance of 3-D Surface Deformation Estimation for Simultaneous Squinted SAR Acquisitions.
IEEE Transactions on Geoscience and Remote Sensing,
56(4):2147-2158,
April 2018.
Keyword(s): SAR Processing,
deformation,
radar imaging,
radar interferometry,
remote sensing by radar,
spaceborne radar,
synthetic aperture radar,
3D mean deformation map retrieval,
3D surface deformation estimation performance,
C band,
L band,
LOSs,
along-track deformation measurement,
angular separations,
atmospheric delay correlation,
atmospheric noise,
differential measurement,
future spaceborne SAR missions,
hybrid Cramer-Rao bound,
interferograms,
lines of sight,
mathematical framework,
multibeam low earth observation missions,
multisatellite earth observation missions,
north-south component sensitivity,
quasisimultaneous squinted synthetic aperture radar interferometric acquisitions,
repeat-pass scenario,
simultaneous SAR image acquisition,
simultaneous squinted SAR acquisitions,
squint angles,
troposphere autocorrelation function,
troposphere-free estimation,
Atmospheric measurements,
Extraterrestrial measurements,
Geometry,
Satellites,
Strain,
Synthetic aperture radar,
Terrestrial atmosphere,
Atmospheric boundary layer (ABL),
differential synthetic aperture radar interferometry (DInSAR),
hybrid Cramer-Rao bound (HCRB),
squinted synthetic aperture radar acquisitions,
synthetic aperture radar (SAR),
troposphere.
Abstract: This paper addresses the performance in the retrieval of 3-D mean deformation maps by exploiting simultaneous or quasi-simultaneous squinted synthetic aperture radar (SAR) interferometric acquisitions in a repeat-pass scenario. In multisatellite or multibeam low earth observation missions, the availability of two (or more) lines of sight (LOSs) allows the simultaneous acquisition of SAR images with different squint angles, hence improving the sensitivity to the north-south component of the deformation. Due to the simultaneity of the acquisitions, the troposphere will be highly correlated and, therefore, will tend to cancel out when performing the differential measurement between the interferograms obtained with the different LOSs, hence resulting in a practically troposphere-free estimation of the along-track deformation measurement. In practice, however, the atmospheric noise in the differential measurement will increase for increasing angular separations. This paper expounds the mathematical framework to derive the performance by properly considering the correlation of the atmospheric delays between the simultaneous acquisitions. To that aim, the hybrid Cramer-Rao bound is exploited making use of the autocorrelation function of the troposphere. Some performance examples are presented in the frame of future spaceborne SAR missions at C and L band. @Article{pratsLopezDekkerDeZanYagueMartinezZonnoRodriguezCassolaTGRS2018Performance3DDeforamtionMultisquintedSpaceborneSAR, author = {Prats-Iraola, Pau and Lopez-Dekker, Paco and De Zan, Francesco and Yague-Martinez, Nestor and Zonno, Mariantonietta and Rodriguez-Cassola, Marc}, title = {Performance of {3-D} Surface Deformation Estimation for Simultaneous Squinted {SAR} Acquisitions}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, year = {2018}, volume = {56}, number = {4}, pages = {2147-2158}, month = apr, issn = {0196-2892}, abstract = {This paper addresses the performance in the retrieval of 3-D mean deformation maps by exploiting simultaneous or quasi-simultaneous squinted synthetic aperture radar (SAR) interferometric acquisitions in a repeat-pass scenario. In multisatellite or multibeam low earth observation missions, the availability of two (or more) lines of sight (LOSs) allows the simultaneous acquisition of SAR images with different squint angles, hence improving the sensitivity to the north-south component of the deformation. Due to the simultaneity of the acquisitions, the troposphere will be highly correlated and, therefore, will tend to cancel out when performing the differential measurement between the interferograms obtained with the different LOSs, hence resulting in a practically troposphere-free estimation of the along-track deformation measurement. In practice, however, the atmospheric noise in the differential measurement will increase for increasing angular separations. This paper expounds the mathematical framework to derive the performance by properly considering the correlation of the atmospheric delays between the simultaneous acquisitions. To that aim, the hybrid Cramer-Rao bound is exploited making use of the autocorrelation function of the troposphere. Some performance examples are presented in the frame of future spaceborne SAR missions at C and L band.}, doi = {10.1109/TGRS.2017.2776140}, file = {:pratsLopezDekkerDeZanYagueMartinezZonnoRodriguezCassolaTGRS2018Performance3DDeforamtionMultisquintedSpaceborneSAR.pdf:PDF}, keywords = {SAR Processing, deformation;radar imaging;radar interferometry;remote sensing by radar;spaceborne radar;synthetic aperture radar;3D mean deformation map retrieval;3D surface deformation estimation performance;C band;L band;LOSs;along-track deformation measurement;angular separations;atmospheric delay correlation;atmospheric noise;differential measurement;future spaceborne SAR missions;hybrid Cramer-Rao bound;interferograms;lines of sight;mathematical framework;multibeam low earth observation missions;multisatellite earth observation missions;north-south component sensitivity;quasisimultaneous squinted synthetic aperture radar interferometric acquisitions;repeat-pass scenario;simultaneous SAR image acquisition;simultaneous squinted SAR acquisitions;squint angles;troposphere autocorrelation function;troposphere-free estimation;Atmospheric measurements;Extraterrestrial measurements;Geometry;Satellites;Strain;Synthetic aperture radar;Terrestrial atmosphere;Atmospheric boundary layer (ABL);differential synthetic aperture radar interferometry (DInSAR);hybrid Cramer-Rao bound (HCRB);squinted synthetic aperture radar acquisitions;synthetic aperture radar (SAR);troposphere}, } -
Meenu Rani,
S. B. Dhok,
and R. B. Deshmukh.
A Systematic Review of Compressive Sensing: Concepts, Implementations and Applications.
IEEE Access,
6:4875-4894,
2018.
Keyword(s): Compressive Sensing,
CS,
Sensors,
Transforms,
Mathematical model,
Sparse matrices,
Compressed sensing,
Reconstruction algorithms,
Image reconstruction,
systematic review,
compressive sensing,
sensing modality,
sparse representation,
compressible representation,
Nyquist sampling rate,
varied reconstruction algorithms,
compressive measurements,
CS acquisition strategies,
signal representation,
transform domain,
sparsity,
random demodulator,
CS reconstruction algorithms,
OMP,
CS applications.
Abstract: Compressive Sensing (CS) is a new sensing modality, which compresses the signal being acquired at the time of sensing. Signals can have sparse or compressible representation either in original domain or in some transform domain. Relying on the sparsity of the signals, CS allows us to sample the signal at a rate much below the Nyquist sampling rate. Also, the varied reconstruction algorithms of CS can faithfully reconstruct the original signal back from fewer compressive measurements. This fact has stimulated research interest toward the use of CS in several fields, such as magnetic resonance imaging, high-speed video acquisition, and ultrawideband communication. This paper reviews the basic theoretical concepts underlying CS. To bridge the gap between theory and practicality of CS, different CS acquisition strategies and reconstruction approaches are elaborated systematically in this paper. The major application areas where CS is currently being used are reviewed here. This paper also highlights some of the challenges and research directions in this field. @Article{raniDhokDeshmukhIEEEAcess2018ASystematicReviewOfCompressiveSensingConceptsImplementationsApplications, author = {Rani, Meenu and Dhok, S. B. and Deshmukh, R. B.}, journal = {IEEE Access}, title = {A Systematic Review of Compressive Sensing: Concepts, Implementations and Applications}, year = {2018}, issn = {2169-3536}, pages = {4875-4894}, volume = {6}, abstract = {Compressive Sensing (CS) is a new sensing modality, which compresses the signal being acquired at the time of sensing. Signals can have sparse or compressible representation either in original domain or in some transform domain. Relying on the sparsity of the signals, CS allows us to sample the signal at a rate much below the Nyquist sampling rate. Also, the varied reconstruction algorithms of CS can faithfully reconstruct the original signal back from fewer compressive measurements. This fact has stimulated research interest toward the use of CS in several fields, such as magnetic resonance imaging, high-speed video acquisition, and ultrawideband communication. This paper reviews the basic theoretical concepts underlying CS. To bridge the gap between theory and practicality of CS, different CS acquisition strategies and reconstruction approaches are elaborated systematically in this paper. The major application areas where CS is currently being used are reviewed here. This paper also highlights some of the challenges and research directions in this field.}, doi = {10.1109/ACCESS.2018.2793851}, file = {:raniDhokDeshmukhIEEEAcess2018ASystematicReviewOfCompressiveSensingConceptsImplementationsApplications.pdf:PDF}, keywords = {Compressive Sensing, CS, Sensors, Transforms, Mathematical model, Sparse matrices, Compressed sensing, Reconstruction algorithms, Image reconstruction, systematic review, compressive sensing, sensing modality, sparse representation, compressible representation, Nyquist sampling rate, varied reconstruction algorithms, compressive measurements, CS acquisition strategies, signal representation, transform domain, sparsity, random demodulator, CS reconstruction algorithms, OMP, CS applications}, owner = {ofrey}, } -
Nida Sakar,
Marc Rodriguez-Cassola,
Pau Prats-Iraola,
Andreas Reigber,
and Alberto Moreira.
Analysis of Geometrical Approximations in Signal Reconstruction Methods for Multistatic SAR Constellations With Large Along-Track Baseline.
IEEE Geoscience and Remote Sensing Letters,
15(6):892-896,
June 2018.
Keyword(s): Doppler effect,
Geometry,
History,
Image reconstruction,
Receivers,
Spaceborne radar,
Synthetic aperture radar,
Digital beamforming,
high-resolution wide-swath (HRWS) radar,
multistatic radar signal processing,
synthetic aperture radar (SAR).
Abstract: Large along-track baselines introduce residual polychromatic quadratic phase components which decrease the performance of state-of-the-art multichannel/multiplatform SAR reconstruction algorithms. This letter investigates the impact of the geometrical approximations in signal reconstruction methods for spaceborne multistatic SAR constellations with large along-track baselines operated with a pulse repetition frequency (PRF) under the Nyquist rate required for a single platform. We characterize and quantify the impact of these approximations, especially severe in the case of kilometric baselines and resolutions around $15lambda$ . Finally, we put forward a generalized range-Doppler strategy to accommodate the geometry of distributed along-track constellations in an accurate manner. @Article{sakarRodriguezCassolaPratsReigberMoreiraGRSL2018GeometricalApproximationsMultistaticAcquisitions, author = {Nida Sakar and Marc Rodriguez-Cassola and Pau Prats-Iraola and Andreas Reigber and Alberto Moreira}, title = {Analysis of Geometrical Approximations in Signal Reconstruction Methods for Multistatic SAR Constellations With Large Along-Track Baseline}, journal = {IEEE Geoscience and Remote Sensing Letters}, year = {2018}, volume = {15}, number = {6}, pages = {892-896}, month = jun, issn = {1545-598X}, abstract = {Large along-track baselines introduce residual polychromatic quadratic phase components which decrease the performance of state-of-the-art multichannel/multiplatform SAR reconstruction algorithms. This letter investigates the impact of the geometrical approximations in signal reconstruction methods for spaceborne multistatic SAR constellations with large along-track baselines operated with a pulse repetition frequency (PRF) under the Nyquist rate required for a single platform. We characterize and quantify the impact of these approximations, especially severe in the case of kilometric baselines and resolutions around $15lambda$ . Finally, we put forward a generalized range-Doppler strategy to accommodate the geometry of distributed along-track constellations in an accurate manner.}, doi = {10.1109/LGRS.2018.2811804}, file = {:sakarRodriguezCassolaPratsReigberMoreiraGRSL2018GeometricalApproximationsMultistaticAcquisitions.pdf:PDF}, keywords = {Doppler effect;Geometry;History;Image reconstruction;Receivers;Spaceborne radar;Synthetic aperture radar;Digital beamforming;high-resolution wide-swath (HRWS) radar;multistatic radar signal processing;synthetic aperture radar (SAR)}, } -
Francescopaolo Sica,
Davide Cozzolino,
Xiao Xiang Zhu,
Luisa Verdoliva,
and Giovanni Poggi.
InSAR-BM3D: A Nonlocal Filter for SAR Interferometric Phase Restoration.
IEEE Transactions on Geoscience and Remote Sensing,
56(6):3456-3467,
June 2018.
Keyword(s): SAR Processing,
InSAR,
SAR Interferometry,
Phase filtering,
InSAR filter,
filter,
AWGN,
filtering theory,
image denoising,
radar imaging,
radar interferometry,
synthetic aperture radar,
InSAR-BM3D,
nonlocal filter,
SAR interferometric phase restoration,
block-matching 3-D,
nonlocal approach,
additive white Gaussian noise image denoising,
synthetic aperture radar,
SAR interferometry signal,
Synthetic aperture radar,
Image restoration,
Wavelet transforms,
AWGN,
Coherence,
Estimation,
Nonlocal filtering,
synthetic aperture radar (SAR),
SAR interferometry (InSAR).
Abstract: The block-matching 3-D (BM3D) algorithm, based on the nonlocal approach, is one of the most effective methods to date for additive white Gaussian noise image denoising. Likewise, its extension to synthetic aperture radar (SAR) amplitude images, SAR-BM3D, is a state-of-the-art SAR despeckling algorithm. In this paper, we further extend BM3D to address the restoration of SAR interferometric phase images. While keeping the general structure of BM3D, its processing steps are modified to take into account the peculiarities of the SAR interferometry signal. Experiments on simulated and real-world Tandem-X SAR interferometric pairs prove the effectiveness of the proposed method. @Article{sicaCozzolinoZhuVerdolivaPoggiTGRS2018InSARBM3DNonlocalFilerForInSAR, author = {Sica, Francescopaolo and Cozzolino, Davide and Zhu, Xiao Xiang and Verdoliva, Luisa and Poggi, Giovanni}, title = {{InSAR-BM3D}: A Nonlocal Filter for {SAR} Interferometric Phase Restoration}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, year = {2018}, volume = {56}, number = {6}, pages = {3456-3467}, month = jun, issn = {0196-2892}, abstract = {The block-matching 3-D (BM3D) algorithm, based on the nonlocal approach, is one of the most effective methods to date for additive white Gaussian noise image denoising. Likewise, its extension to synthetic aperture radar (SAR) amplitude images, SAR-BM3D, is a state-of-the-art SAR despeckling algorithm. In this paper, we further extend BM3D to address the restoration of SAR interferometric phase images. While keeping the general structure of BM3D, its processing steps are modified to take into account the peculiarities of the SAR interferometry signal. Experiments on simulated and real-world Tandem-X SAR interferometric pairs prove the effectiveness of the proposed method.}, doi = {10.1109/TGRS.2018.2800087}, file = {:sicaCozzolinoZhuVerdolivaPoggiTGRS2018InSARBM3DNonlocalFilerForInSAR.pdf:PDF}, keywords = {SAR Processing, InSAR, SAR Interferometry, Phase filtering, InSAR filter, filter, AWGN;filtering theory;image denoising;radar imaging;radar interferometry;synthetic aperture radar;InSAR-BM3D;nonlocal filter;SAR interferometric phase restoration;block-matching 3-D;nonlocal approach;additive white Gaussian noise image denoising;synthetic aperture radar;SAR interferometry signal;Synthetic aperture radar;Image restoration;Wavelet transforms;AWGN;Coherence;Estimation;Nonlocal filtering;synthetic aperture radar (SAR);SAR interferometry (InSAR)}, owner = {ofrey}, } -
Muhammad Adnan Siddique,
Urs Wegmuller,
Irena Hajnsek,
and Othmar Frey.
SAR Tomography as an Add-On to PSI: Detection of Coherent Scatterers in the Presence of Phase Instabilities.
Remote Sensing,
10(7):1014,
2018.
Keyword(s): SAR Processing,
SAR tomography,
Synthetic aperture radar (SAR),
SAR Interferometry,
InSAR,
interferometric stacking,
persistent scatterer interferometry,
PSI,
spaceborne SAR radar interferometry,
spaceborne radar,
X-Band,
TerraSAR-X,
synthetic aperture radar,
tomography,
3-D point cloud retrieval,
SAR tomography based 3-D point cloud extraction,
high-resolution spaceborne SAR,
Barcelona,
interferometric stack,
layover scenario case,
persistent scatterer interferometry,
PSI,
point-like scatterer,
processing approach,
Urban Remote Sensing,
Spaceborne radar,
Synthetic aperture radar,
Three-dimensional displays,
Tomography,
3-D point cloud,
SAR interferometry,
deformation,
displacement,
subsidence,
detection,
urban deformation monitoring,
radar interferometry,
displacement mapping,
spaceborne SAR,
differential interferometry,
differential tomography,
coherent scatterer detection.
Abstract: The estimation of deformation parameters using persistent scatterer interferometry (PSI) is limited to single dominant coherent scatterers. As such, it rejects layovers wherein multiple scatterers are interfering in the same range-azimuth resolution cell. Differential synthetic aperture radar (SAR) tomography can improve deformation sampling as it has the ability to resolve layovers by separating the interfering scatterers. In this way, both PSI and tomography inevitably require a means to detect coherent scatterers, i.e., to perform hypothesis testing to decide whether a given candidate scatterer is coherent. This paper reports the application of a detection strategy in the context of tomography as an add-on to PSI. As the performance of a detector is typically linked to the statistical description of the underlying mathematical model, we investigate how the statistics of the phase instabilities in the PSI analysis are carried forward to the subsequent tomographic analysis. While phase instabilities in PSI are generally modeled as an additive noise term in the interferometric phase model, their impact in SAR tomography manifests as a multiplicative disturbance. The detection strategy proposed in this paper allows extending the same quality considerations as used in the prior PSI processing (in terms of the dispersion of the residual phase) to the subsequent tomographic analysis. In particular, the hypothesis testing for the detection of coherent scatterers is implemented such that the expected probability of false alarm is consistent between PSI and tomography. The investigation is supported with empirical analyses on an interferometric data stack comprising 50 TerraSAR-X acquisitions in stripmap mode, over the city of Barcelona, Spain, from 2007-2012. @Article{siddiqueWegmullerHajnsekFreyRemoteSensing2018SARTomoPSIDetectionInPresenceOfPhaseInstabilities, author = {Siddique, Muhammad Adnan and Wegmuller, Urs and Hajnsek, Irena and Frey, Othmar}, journal = {Remote Sensing}, title = {{SAR} Tomography as an Add-On to {PSI}: Detection of Coherent Scatterers in the Presence of Phase Instabilities}, year = {2018}, issn = {2072-4292}, number = {7}, pages = {1014}, volume = {10}, abstract = {The estimation of deformation parameters using persistent scatterer interferometry (PSI) is limited to single dominant coherent scatterers. As such, it rejects layovers wherein multiple scatterers are interfering in the same range-azimuth resolution cell. Differential synthetic aperture radar (SAR) tomography can improve deformation sampling as it has the ability to resolve layovers by separating the interfering scatterers. In this way, both PSI and tomography inevitably require a means to detect coherent scatterers, i.e., to perform hypothesis testing to decide whether a given candidate scatterer is coherent. This paper reports the application of a detection strategy in the context of tomography as an add-on to PSI. As the performance of a detector is typically linked to the statistical description of the underlying mathematical model, we investigate how the statistics of the phase instabilities in the PSI analysis are carried forward to the subsequent tomographic analysis. While phase instabilities in PSI are generally modeled as an additive noise term in the interferometric phase model, their impact in SAR tomography manifests as a multiplicative disturbance. The detection strategy proposed in this paper allows extending the same quality considerations as used in the prior PSI processing (in terms of the dispersion of the residual phase) to the subsequent tomographic analysis. In particular, the hypothesis testing for the detection of coherent scatterers is implemented such that the expected probability of false alarm is consistent between PSI and tomography. The investigation is supported with empirical analyses on an interferometric data stack comprising 50 TerraSAR-X acquisitions in stripmap mode, over the city of Barcelona, Spain, from 2007-2012.}, doi = {10.3390/rs10071014}, file = {:siddiqueWegmullerHajnsekFreyRemoteSensing2018SARTomoPSIDetectionInPresenceOfPhaseInstabilities.pdf:PDF}, keywords = {SAR Processing, SAR tomography; Synthetic aperture radar (SAR); SAR Interferometry, InSAR, interferometric stacking;persistent scatterer interferometry; PSI, spaceborne SAR radar interferometry;spaceborne radar; X-Band, TerraSAR-X, synthetic aperture radar;tomography;3-D point cloud retrieval; SAR tomography based 3-D point cloud extraction; high-resolution spaceborne SAR, Barcelona, interferometric stack;layover scenario case;persistent scatterer interferometry; PSI, point-like scatterer;processing approach;Urban Remote Sensing; Spaceborne radar;Synthetic aperture radar;Three-dimensional displays;Tomography; 3-D point cloud;SAR interferometry, deformation, displacement, subsidence, detection, urban deformation monitoring; radar interferometry; displacement mapping; spaceborne SAR; differential interferometry; differential tomography, coherent scatterer detection}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueWegmullerHajnsekFreyRemoteSensing2018SARTomoPSIDetectionInPresenceOfPhaseInstabilities.pdf}, url = {http://www.mdpi.com/2072-4292/10/7/1014}, } -
Ladina Steiner,
Michael Meindl,
Charles Fierz,
and Alain Geiger.
An assessment of sub-snow GPS for quantification of snow water equivalent.
The Cryosphere,
12(10):3161-3175,
2018.
Keyword(s): GNSS,
GPS,
Snow-water equivalent,
SWE,
Submerged antennas.
Abstract: Global Navigation Satellite Systems (GNSS) contribute to various Earth observation applications. The present study investigates the potential and limitations of the Global Positioning System (GPS) to estimate in-situ water equivalents of the snow cover (snow water equivalent, SWE) by using buried GPS antennas. GPS-derived SWE is estimated over three seasons (2015/16-2017/18) at a high Alpine test site in Switzerland. Results are validated against state-of-the-art reference sensors: snow scale, snow pillow, and manual observations. SWE is estimated with a high correspondence to the reference sensors for all three seasons. Results agree with a median relative bias below 10% and are highly correlated to the mean of the three reference sensors. The sensitivity of the SWE quantification is assessed for different GPS ambiguity resolution techniques, as the results strongly depend on the GPS processing. @Article{steinerMeindlFierzGeigerCryosphere2018GNSSforSWE, author = {Steiner, Ladina and Meindl, Michael and Fierz, Charles and Geiger, Alain}, title = {An assessment of sub-snow {GPS} for quantification of snow water equivalent}, journal = {The Cryosphere}, year = {2018}, volume = {12}, number = {10}, pages = {3161--3175}, abstract = {Global Navigation Satellite Systems (GNSS) contribute to various Earth observation applications. The present study investigates the potential and limitations of the Global Positioning System (GPS) to estimate in-situ water equivalents of the snow cover (snow water equivalent, SWE) by using buried GPS antennas. GPS-derived SWE is estimated over three seasons (2015/16-2017/18) at a high Alpine test site in Switzerland. Results are validated against state-of-the-art reference sensors: snow scale, snow pillow, and manual observations. SWE is estimated with a high correspondence to the reference sensors for all three seasons. Results agree with a median relative bias below 10% and are highly correlated to the mean of the three reference sensors. The sensitivity of the SWE quantification is assessed for different GPS ambiguity resolution techniques, as the results strongly depend on the GPS processing.}, doi = {10.5194/tc-12-3161-2018}, file = {:steinerMeindlFierzGeigerCryosphere2018GNSSforSWE.pdf:PDF}, keywords = {GNSS, GPS, Snow-water equivalent, SWE, Submerged antennas}, owner = {ofrey}, url = {https://www.the-cryosphere.net/12/3161/2018/}, } -
Marivi Tello-Alonso,
Victor Cazcarra-Bes,
Matteo Pardini,
and K. Papathanassiou.
Forest Structure Characterization From SAR Tomography at L-Band.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
11(10):3402-3414,
October 2018.
Keyword(s): SAR Processing,
SAR Tomography,
forestry,
optical radar,
radar imaging,
radar interferometry,
radar polarimetry,
remote sensing by laser beam,
remote sensing by radar,
synthetic aperture radar,
vegetation mapping,
3-D forest monitoring,
radar reflectivity,
physical forest structure,
tomographic SAR data,
vertical structure index,
inventory data,
spatial distribution,
experimental tomographic L-band data,
vertical structure indices,
vertical profiles,
forest structure indices,
forest structure characterization,
SAR tomography,
synthetic aperture radar remote sensing configurations,
high spatial resolution,
temporal resolution,
tomographic SAR techniques,
correlation coefficients,
Forestry,
Vegetation,
Synthetic aperture radar,
Tomography,
Indexes,
L-band,
Forest structure,
synthetic aperture radar,
tomography.
Abstract: Synthetic aperture radar (SAR) remote sensing configurations are able to provide continuous measurements on global scales sensitive to the vertical structure of forests with a high spatial and temporal resolution. Furthermore, the development of tomographic SAR techniques allows the reconstruction of the three-dimensional (3-D) radar reflectivity opening the door for 3-D forest monitoring. However, the link between 3-D radar reflectivity and 3-D forest structure is not yet established. In this sense, this paper introduced a framework that allows a qualitative and quantitative interpretation of physical forest structure from tomographic SAR data at L-band. For this, forest structure is parameterized into a set of a horizontal and a vertical structure index. From inventory data, both indices can be derived from the spatial distribution and the dimensions of the trees. Similarly, two structure indices are derived from the 3-D spatial distribution of the local maxima of the reconstructed 3-D radar reflectivity profiles at L-band. The proposed methodology is tested by means of experimental tomographic L-band data acquired over the temperate forest site of Traunstein in Germany. The obtained horizontal and vertical structure indices are validated against the corresponding estimates obtained from inventory measurements and against the same indices derived from the vertical profiles of airborne Lidar data. The high correlation between the forest structure indices obtained from these three different data sources (expressed by correlation coefficients between 0.75 and 0.87) indicates the potential of the proposed framework. @Article{telloAlonsoCazcarraBesPardiniPapathanassiouJSTARS2018ForestStructureLBandSARTomography, author = {Tello-Alonso, Marivi and Cazcarra-Bes, Victor and Pardini, Matteo and Papathanassiou, K.}, title = {Forest Structure Characterization From SAR Tomography at L-Band}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, year = {2018}, volume = {11}, number = {10}, pages = {3402-3414}, month = {Oct}, abstract = {Synthetic aperture radar (SAR) remote sensing configurations are able to provide continuous measurements on global scales sensitive to the vertical structure of forests with a high spatial and temporal resolution. Furthermore, the development of tomographic SAR techniques allows the reconstruction of the three-dimensional (3-D) radar reflectivity opening the door for 3-D forest monitoring. However, the link between 3-D radar reflectivity and 3-D forest structure is not yet established. In this sense, this paper introduced a framework that allows a qualitative and quantitative interpretation of physical forest structure from tomographic SAR data at L-band. For this, forest structure is parameterized into a set of a horizontal and a vertical structure index. From inventory data, both indices can be derived from the spatial distribution and the dimensions of the trees. Similarly, two structure indices are derived from the 3-D spatial distribution of the local maxima of the reconstructed 3-D radar reflectivity profiles at L-band. The proposed methodology is tested by means of experimental tomographic L-band data acquired over the temperate forest site of Traunstein in Germany. The obtained horizontal and vertical structure indices are validated against the corresponding estimates obtained from inventory measurements and against the same indices derived from the vertical profiles of airborne Lidar data. The high correlation between the forest structure indices obtained from these three different data sources (expressed by correlation coefficients between 0.75 and 0.87) indicates the potential of the proposed framework.}, doi = {10.1109/JSTARS.2018.2859050}, file = {:telloAlonsoCazcarraBesPardiniPapathanassiouJSTARS2018ForestStructureLBandSARTomography.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, forestry;optical radar;radar imaging;radar interferometry;radar polarimetry;remote sensing by laser beam;remote sensing by radar;synthetic aperture radar;vegetation mapping;3-D forest monitoring;radar reflectivity;physical forest structure;tomographic SAR data;vertical structure index;inventory data;spatial distribution;experimental tomographic L-band data;vertical structure indices;vertical profiles;forest structure indices;forest structure characterization;SAR tomography;synthetic aperture radar remote sensing configurations;high spatial resolution;temporal resolution;tomographic SAR techniques;correlation coefficients;Forestry;Vegetation;Synthetic aperture radar;Tomography;Indexes;L-band;Forest structure;synthetic aperture radar;tomography}, owner = {ofrey}, } -
Lars M. H. Ulander,
Albert R. Monteith,
Macej J. Soja,
and Leif E. B. Eriksson.
Multiport Vector Network Analyzer Radar for Tomographic Forest Scattering Measurements.
IEEE Geoscience and Remote Sensing Letters,
15(12):1897-1901,
December 2018.
Keyword(s): SAR Tomography,
BorealScat,
antenna arrays,
multiport networks,
network analysers,
radar antennas,
radar imaging,
S-parameters,
tomographic forest scattering measurements,
C-band radar,
BorealScat,
radar tomography,
vertical antenna array,
vertical scattering distribution,
temporal decorrelation,
reflected signals,
20-port vector network analyzer,
stepped-frequency waveform,
20-element arrays,
radar measurements,
hemiboreal forest,
tomographic imaging capabilities,
multiport VNA tomography results,
2-port VNA measurement scheme,
multiport vector network analyzer radar,
P-band radar,
L-band radar,
polarimetric time-series measurements,
Antenna measurements,
Antenna arrays,
Forestry,
Tomography,
Radar,
Radar antennas,
Switches,
BorealScat,
forest,
polarimetry,
radar,
scattering,
time series,
tomography,
vector network analyzer (VNA).
Abstract: We describe a P-, L- and C-band radar, BorealScat, designed for polarimetric time-series measurements of forests. Radar tomography is implemented with a vertical antenna array, which provides measurements of the vertical scattering distribution. To minimize temporal decorrelation, the radar performs simultaneous measurements of the reflected signals using all array elements. The system is implemented using a 20-port vector network analyzer (VNA) and a stepped-frequency waveform. It has two 20-element arrays: one array optimized for P- and L-bands and one for C-band. The arrays are installed on a 50-m high tower and radar measurements are collected over a hemiboreal forest stand. We discuss several design issues and demonstrate some tomographic imaging capabilities. The multiport VNA tomography results are compared with results from the system operating in the slower 2-port VNA measurement scheme. @Article{ulanderMonteithSojaErikssonGRSL2018MultiportVNAForBorealScatForestScattering, author = {Ulander, Lars M. H. and Monteith, Albert R. and Soja, Macej J. and Eriksson, Leif E. B.}, journal = {IEEE Geoscience and Remote Sensing Letters}, title = {Multiport Vector Network Analyzer Radar for Tomographic Forest Scattering Measurements}, year = {2018}, issn = {1558-0571}, month = {Dec}, number = {12}, pages = {1897-1901}, volume = {15}, abstract = {We describe a P-, L- and C-band radar, BorealScat, designed for polarimetric time-series measurements of forests. Radar tomography is implemented with a vertical antenna array, which provides measurements of the vertical scattering distribution. To minimize temporal decorrelation, the radar performs simultaneous measurements of the reflected signals using all array elements. The system is implemented using a 20-port vector network analyzer (VNA) and a stepped-frequency waveform. It has two 20-element arrays: one array optimized for P- and L-bands and one for C-band. The arrays are installed on a 50-m high tower and radar measurements are collected over a hemiboreal forest stand. We discuss several design issues and demonstrate some tomographic imaging capabilities. The multiport VNA tomography results are compared with results from the system operating in the slower 2-port VNA measurement scheme.}, doi = {10.1109/LGRS.2018.2865673}, file = {:ulanderMonteithSojaErikssonGRSL2018MultiportVNAForBorealScatForestScattering.pdf:PDF}, keywords = {SAR Tomography, BorealScat, antenna arrays;multiport networks;network analysers;radar antennas;radar imaging;S-parameters;tomographic forest scattering measurements;C-band radar;BorealScat;radar tomography;vertical antenna array;vertical scattering distribution;temporal decorrelation;reflected signals;20-port vector network analyzer;stepped-frequency waveform;20-element arrays;radar measurements;hemiboreal forest;tomographic imaging capabilities;multiport VNA tomography results;2-port VNA measurement scheme;multiport vector network analyzer radar;P-band radar;L-band radar;polarimetric time-series measurements;Antenna measurements;Antenna arrays;Forestry;Tomography;Radar;Radar antennas;Switches;BorealScat;forest;polarimetry;radar;scattering;time series;tomography;vector network analyzer (VNA)}, owner = {ofrey}, } -
Urs Wegmuller,
Charles Werner,
Othmar Frey,
Christophe Magnard,
and Tazio Strozzi.
Reformulating the Split-Spectrum Method to Facilitate the Estimation and Compensation of the Ionospheric Phase in SAR Interferograms.
Procedia Computer Science,
pp 318-325,
2018.
Keyword(s): SAR Processing,
Ionosphere,
Ionospheric Path Delay,
split-beam interferometry,
SBI,
ionospheric electromagnetic wave propagation,
ionospheric techniques,
radar interferometry,
remote sensing by radar,
split beam interferograms,
along track ground displacement estimation,
azimuth spectrum band pass filtering,
directional scattering identification,
ionospheric path delay estimation,
long baseline pair coherence estimation,
split beam interferometry,
Azimuth,
Band pass filters,
Coherence,
Delay,
Ionosphere,
Time series analysis.
@Article{wegmullerWernerFreyMagnardStrozziProcediaCS2018SplitSpectrumIonosphereReformulation, author = {Wegmuller, Urs and Werner, Charles and Frey, Othmar and Magnard, Christophe and Strozzi, Tazio}, title = {Reformulating the Split-Spectrum Method to Facilitate the Estimation and Compensation of the Ionospheric Phase in {SAR} Interferograms}, journal = {Procedia Computer Science}, year = {2018}, pages = {318-325}, doi = {10.1016/j.procs.2018.10.045}, file = {:wegmullerWernerFreyMagnardStrozziProcediaCS2018SplitSpectrumIonosphereReformulation.pdf:PDF}, keywords = {SAR Processing, Ionosphere, Ionospheric Path Delay, split-beam interferometry, SBI, ionospheric electromagnetic wave propagation;ionospheric techniques;radar interferometry;remote sensing by radar;split beam interferograms;along track ground displacement estimation;azimuth spectrum band pass filtering;directional scattering identification;ionospheric path delay estimation;long baseline pair coherence estimation;split beam interferometry;Azimuth;Band pass filters;Coherence;Delay;Ionosphere;Time series analysis}, owner = {ofrey}, }
Conference articles
-
Simone Baffelli,
Othmar Frey,
and Irena Hajnsek.
Geostatistical Analysis and Mitigation of Atmosphere Induced Phase in Terrestrial Radar Interferometric Observations of an Alpine Glacier.
In Proc. of EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar,
pages 626-631,
2018.
Keyword(s): Radar Interferometry,
Terrestrial Radar Interferometry,
TRI,
Ground-based radar,
Interferometry,
glacier velocity,
atmospheric phase,
mitigation of atmospheric phase,
APS,
Bisgletscher,
Radar time series,
GPRI,
Gamma Portable Radar Interferometer.
Abstract: Terrestrial Radar Interferometry is used to map surface displacement velocites with high temporal resolution, irrespective of sunlight and cloud cover. The main factor limiting estimation accuracy are variations in the atmospheric refractive index, observed as atmospheric phase screens (APS). A statistical model for APS assuming a separable spatio-temporal covariance structure is described. It facilitates the extrapolation of the APS from observations at persistent scatterers (PS) using regression-Kriging, which is followed by a timeseries inversion to estimate the surface velocity. A statistical analysis of the APS is performed using a Ku-Band radar timeseries of Bisgletscher, a glacier in the Southwestern Swiss Alps. The results show that, while some non-stationarity in the covariance structure is observed at large timescales, the covariance models obtained assuming separability perform well in APS mitigation using regression-Kriging. @InProceedings{baffelliFreyHajnsekEUSAR2018GeostatsMitigationTerrestrialRadarInterferometryBisgletscher, author = {Simone Baffelli and Othmar Frey and Irena Hajnsek}, booktitle = {Proc. of EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar}, title = {Geostatistical Analysis and Mitigation of Atmosphere Induced Phase in Terrestrial Radar Interferometric Observations of an Alpine Glacier}, year = {2018}, pages = {626--631}, abstract = {Terrestrial Radar Interferometry is used to map surface displacement velocites with high temporal resolution, irrespective of sunlight and cloud cover. The main factor limiting estimation accuracy are variations in the atmospheric refractive index, observed as atmospheric phase screens (APS). A statistical model for APS assuming a separable spatio-temporal covariance structure is described. It facilitates the extrapolation of the APS from observations at persistent scatterers (PS) using regression-Kriging, which is followed by a timeseries inversion to estimate the surface velocity. A statistical analysis of the APS is performed using a Ku-Band radar timeseries of Bisgletscher, a glacier in the Southwestern Swiss Alps. The results show that, while some non-stationarity in the covariance structure is observed at large timescales, the covariance models obtained assuming separability perform well in APS mitigation using regression-Kriging.}, file = {:baffelliFreyHajnsekEUSAR2018GeostatsMitigationTerrestrialRadarInterferometryBisgletscher.pdf:PDF}, keywords = {Radar Interferometry, Terrestrial Radar Interferometry, TRI, Ground-based radar, Interferometry, glacier velocity, atmospheric phase, mitigation of atmospheric phase, APS, Bisgletscher, Radar time series, GPRI, Gamma Portable Radar Interferometer}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/baffelliFreyHajnsekEUSAR2018GeostatsMitigationTerrestrialRadarInterferometryBisgletscher.pdf}, } -
Simone Baffelli,
Othmar Frey,
and Irena Hajnsek.
Geostatistical Analysis and Mitigation of Atmospheric Phase Screens in Ku-Band Terrestrial Radar Interferometry.
In Proc. IEEE Int. Geosci. Remote Sens. Symp.,
pages 6504-6507,
2018.
Keyword(s): Radar Interferometry,
Terrestrial Radar Interferometry,
TRI,
Ground-based radar,
Interferometry,
glacier velocity,
atmospheric phase,
mitigation of atmospheric phase,
APS,
Bisgletscher,
Radar time series,
GPRI,
Gamma Portable Radar Interferometer.
Abstract: A geostatistical analysis of the atmospheric phase screen (APS) affecting Ku-Band terrestrial radar interferometric (TRI) observations of a fast-flowing alpine glacier is made assuming a separable spatio-temporal covariance structure. Such a structure facilitates the mitigation of APS: the atmospheric phase affecting individual interferograms can be extrapolated form a set of persistent scatterers (PS) using regression-Kriging. After removing this estimate the residual APS is only correlated in time; its effect on surface displacement estimation is mitigated with a generalized least squares (GLS) inversion employing an estimate of the temporal covariance of the APS. The applicability of a separable covariance structure and the performance of the APS correction method are assessed on a TRI timeseries of Bisgletscher, a glacier in the southwestern Swiss Alps. @InProceedings{baffelliFreyHajnsekIGARSS2018GeostatisticalMitigationOfAPSinTerrestrialRadarInterferometry, author = {Simone Baffelli and Othmar Frey and Irena Hajnsek}, booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.}, title = {Geostatistical Analysis and Mitigation of Atmospheric Phase Screens in {Ku}-Band Terrestrial Radar Interferometry}, year = {2018}, pages = {6504--6507}, abstract = {A geostatistical analysis of the atmospheric phase screen (APS) affecting Ku-Band terrestrial radar interferometric (TRI) observations of a fast-flowing alpine glacier is made assuming a separable spatio-temporal covariance structure. Such a structure facilitates the mitigation of APS: the atmospheric phase affecting individual interferograms can be extrapolated form a set of persistent scatterers (PS) using regression-Kriging. After removing this estimate the residual APS is only correlated in time; its effect on surface displacement estimation is mitigated with a generalized least squares (GLS) inversion employing an estimate of the temporal covariance of the APS. The applicability of a separable covariance structure and the performance of the APS correction method are assessed on a TRI timeseries of Bisgletscher, a glacier in the southwestern Swiss Alps.}, doi = {10.1109/IGARSS.2018.8517479}, file = {:baffelliFreyHajnsekIGARSS2018GeostatisticalMitigationOfAPSinTerrestrialRadarInterferometry.pdf:PDF}, keywords = {Radar Interferometry, Terrestrial Radar Interferometry, TRI, Ground-based radar, Interferometry, glacier velocity, atmospheric phase, mitigation of atmospheric phase, APS, Bisgletscher, Radar time series, GPRI, Gamma Portable Radar Interferometer}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/baffelliFreyHajnsekIGARSS2018GeostatisticalMitigationOfAPSinTerrestrialRadarInterferometry.pdf}, } -
Roberto Coscione,
Irena Hajnsek,
and Othmar Frey.
An experimental car-borne SAR System: measurement setup and positioning error analysis.
In Proc. IEEE Int. Geosci. Remote Sens. Symp.,
pages 6364-6367,
2018.
Keyword(s): SAR Processing,
Time-Domain Back-Projection,
TDBP,
dechirp-on-receive,
FMCW,
Frequency-modulated continous wave,
Ground-based SAR,
car-borne SAR,
CARSAR,
InSAR,
DInSAR,
geophysical techniques,
ground-based SAR system,
radar interferometry,
synthetic aperture radar,
GAMMA Portable Radar Interferometer (GPRI),
GPRI,
GPRI-II,
interferometric technique,
Coherence,
Correlation,
Interferometry,
agile platform,
airborne SAR,
Inertial Naviation System (INS),
Global Navigation Satellite System (GNSS),
INS/GNSS,
iMAR.
Abstract: Repeat-pass differential SAR interferometry (DInSAR) using spaceborne SAR data or stationary terrestrial radar data is an established technique to measure surface displacements. However, repeat-pass DInSAR from agile platforms (airborne/car-borne) is challenging due to residual motion errors. This is particularly true for high-frequency radar where motion errors of few millimeters represent a non-negligible fraction of the wavelength. In this paper, an experimental car-borne SAR system is presented. Such a system is complementary to the existing solutions (namely spaceborne, airborne, and terrestrial systems) in terms of geometry of acquisition, and flexibility in the selection of temporal baselines and location of the acquisitions. To meet the need of consistent and precise trajectory information, proper postprocessing procedures must be applied to the raw positioning data collected from the inertial navigation system (INS) and the global positioning system (GNSS). A viable procedure is here presented and first results discussed. @InProceedings{coscioneHajnsekFreyIGARSS2018CarborneSARPositioningErrorAnalysis, author = {Roberto Coscione and Irena Hajnsek and Othmar Frey}, booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.}, title = {An experimental car-borne SAR System: measurement setup and positioning error analysis}, year = {2018}, pages = {6364--6367}, abstract = {Repeat-pass differential SAR interferometry (DInSAR) using spaceborne SAR data or stationary terrestrial radar data is an established technique to measure surface displacements. However, repeat-pass DInSAR from agile platforms (airborne/car-borne) is challenging due to residual motion errors. This is particularly true for high-frequency radar where motion errors of few millimeters represent a non-negligible fraction of the wavelength. In this paper, an experimental car-borne SAR system is presented. Such a system is complementary to the existing solutions (namely spaceborne, airborne, and terrestrial systems) in terms of geometry of acquisition, and flexibility in the selection of temporal baselines and location of the acquisitions. To meet the need of consistent and precise trajectory information, proper postprocessing procedures must be applied to the raw positioning data collected from the inertial navigation system (INS) and the global positioning system (GNSS). A viable procedure is here presented and first results discussed.}, doi = {10.1109/IGARSS.2018.8519408}, file = {:coscioneHajnsekFreyIGARSS2018CarborneSARPositioningErrorAnalysis.pdf:PDF}, keywords = {SAR Processing, Time-Domain Back-Projection, TDBP, dechirp-on-receive, FMCW, Frequency-modulated continous wave, Ground-based SAR, car-borne SAR, CARSAR, InSAR, DInSAR, geophysical techniques; ground-based SAR system, radar interferometry;synthetic aperture radar; GAMMA Portable Radar Interferometer (GPRI), GPRI, GPRI-II, interferometric technique; Coherence;Correlation;Interferometry, agile platform, airborne SAR, Inertial Naviation System (INS), Global Navigation Satellite System (GNSS), INS/GNSS, iMAR}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/coscioneHajnsekFreyIGARSS2018CarborneSARPositioningErrorAnalysis.pdf}, } -
Othmar Frey,
Charles L. Werner,
Rafael Caduff,
and Andreas Wiesmann.
Tomographic profiling with SnowScat within the ESA SnowLab Campaign: Time Series of Snow Profiles Over Three Snow Seasons.
In Proc. IEEE Int. Geosci. Remote Sens. Symp.,
pages 6512-6515,
2018.
Keyword(s): SAR Processing,
SAR Tomography,
Tomographic profiling,
SnowScat,
ESA,
European Space Agency,
X-Band,
Ku-Band,
Polarimetry,
ground-based radar,
Snow,
Snowpack,
geophysical signal processing,
radar polarimetry,
synthetic aperture radar.
Abstract: As part of the ESA SnowLab campaign the SnowScat device, a terrestrial stepped-frequency continuous wave (SFCW) scatterometer which supports fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz, was operated in tomographic profiling mode. In this tomographic profiling mode the SnowScat device is subsequently displaced in elevation direction to obtain a high-resolution not only in range direction but also along elevation. This leads to two-dimensional vertical profiles of a snowpack, which means that radar backscatter, co-polar phase difference, interferometric phase and coherence can be distinguished also along the vertical dimension of the snowpack. In this paper, we provide a summary and a few examples of a time series of tomographic measurements of snow obtained within the ESA SnowLab campaign at two different locations in the Swiss Alps during three snow seasons. @InProceedings{freyWernerCaduffWiesmannIGARSS2018SnowScatTomoTimeSeries, author = {Othmar Frey and Charles L. Werner and Rafael Caduff and Andreas Wiesmann}, booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.}, title = {Tomographic profiling with {SnowScat} within the {ESA} {SnowLab} Campaign: Time Series of Snow Profiles Over Three Snow Seasons}, year = {2018}, pages = {6512-6515}, abstract = {As part of the ESA SnowLab campaign the SnowScat device, a terrestrial stepped-frequency continuous wave (SFCW) scatterometer which supports fully-polarimetric measurements within a frequency band from 9.2 to 17.8 GHz, was operated in tomographic profiling mode. In this tomographic profiling mode the SnowScat device is subsequently displaced in elevation direction to obtain a high-resolution not only in range direction but also along elevation. This leads to two-dimensional vertical profiles of a snowpack, which means that radar backscatter, co-polar phase difference, interferometric phase and coherence can be distinguished also along the vertical dimension of the snowpack. In this paper, we provide a summary and a few examples of a time series of tomographic measurements of snow obtained within the ESA SnowLab campaign at two different locations in the Swiss Alps during three snow seasons.}, doi = {10.1109/IGARSS.2018.8517692}, file = {:freyWernerCaduffWiesmannIGARSS2018SnowScatTomoTimeSeries.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band, Polarimetry, ground-based radar; Snow, Snowpack, geophysical signal processing;radar polarimetry;synthetic aperture radar}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/freyWernerCaduffWiesmannIGARSS2018SnowScatTomoTimeSeries.pdf}, } -
Othmar Frey,
Charles L. Werner,
Irena Hajnsek,
and Roberto Coscione.
A car-borne SAR system for interferometric measurements: development status and system enhancements.
In Proc. IEEE Int. Geosci. Remote Sens. Symp.,
pages 6508-6511,
2018.
Keyword(s): SAR Processing,
Time-Domain Back-Projection,
TDBP,
dechirp-on-receive,
FMCW,
Frequency-modulated continous wave,
Ground-based SAR,
car-borne SAR,
CARSAR,
InSAR,
DInSAR,
geophysical techniques,
ground-based SAR system,
radar interferometry,
synthetic aperture radar,
GAMMA Portable Radar Interferometer (GPRI),
GPRI,
GPRI-II,
interferometric technique,
Coherence,
Correlation,
Interferometry,
agile platform,
airborne SAR.
Abstract: Terrestrial radar systems are used operationally for area-wide measurement and monitoring of surface displacements on steep slopes, as prevalent in mountainous areas or also in open pit mines. One limitation of these terrestrial systems is the decreasing cross-range resolution with increasing distance of observation due to the limited antenna size of the real aperture radar or the limited synthetic aperture of the quasi-stationary SAR systems. Recently, we have conducted a first experiment using a car-borne SAR system at Ku-band, demonstrating the time-domain back-projection (TDBP) focusing capability for the FMCW case and single-pass interferometric capability of our experimental Ku-band car-borne SAR system. The cross-range spatial resolution provided by such a car-based SAR system is potentially independent from the distance of observation, given that an adequate sensor trajectory can be built. In this paper, we give (1) an overview of the updated system hardware (radar setup and high-precision combined INS/GNSS positioning and attitude determination), and (2) present SAR imagery obtained with the updated prototype Ku-band car-borne SAR system. @InProceedings{freyWernerHajnsekCoscioneIGARSS2018CarborneSARforInSARDevelopmentAndEnhancements, author = {Othmar Frey and Charles L. Werner and Irena Hajnsek and Roberto Coscione}, booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.}, title = {A car-borne {SAR} system for interferometric measurements: development status and system enhancements}, year = {2018}, pages = {6508--6511}, abstract = {Terrestrial radar systems are used operationally for area-wide measurement and monitoring of surface displacements on steep slopes, as prevalent in mountainous areas or also in open pit mines. One limitation of these terrestrial systems is the decreasing cross-range resolution with increasing distance of observation due to the limited antenna size of the real aperture radar or the limited synthetic aperture of the quasi-stationary SAR systems. Recently, we have conducted a first experiment using a car-borne SAR system at Ku-band, demonstrating the time-domain back-projection (TDBP) focusing capability for the FMCW case and single-pass interferometric capability of our experimental Ku-band car-borne SAR system. The cross-range spatial resolution provided by such a car-based SAR system is potentially independent from the distance of observation, given that an adequate sensor trajectory can be built. In this paper, we give (1) an overview of the updated system hardware (radar setup and high-precision combined INS/GNSS positioning and attitude determination), and (2) present SAR imagery obtained with the updated prototype Ku-band car-borne SAR system.}, doi = {10.1109/IGARSS.2018.8518840}, file = {:freyWernerHajnsekCoscioneIGARSS2018CarborneSARforInSARDevelopmentAndEnhancements.pdf:PDF}, keywords = {SAR Processing, Time-Domain Back-Projection, TDBP, dechirp-on-receive, FMCW, Frequency-modulated continous wave, Ground-based SAR, car-borne SAR, CARSAR, InSAR, DInSAR, geophysical techniques; ground-based SAR system, radar interferometry;synthetic aperture radar; GAMMA Portable Radar Interferometer (GPRI), GPRI, GPRI-II, interferometric technique; Coherence;Correlation;Interferometry, agile platform, airborne SAR}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/freyWernerHajnsekCoscioneIGARSS2018CarborneSARforInSARDevelopmentAndEnhancements.pdf}, } -
C. Magnard,
U. Wegmuller,
C. Werner,
F. Bonvin,
and E. Meier.
Planning tool for SAR missions.
In Proc. European Conf. Synthetic Aperture Radar,
pages 1052-1057,
2018.
Keyword(s): Image segmentation,
Optical variables measurement,
Radar imaging,
Image quality parameters,
Incidence angles,
Planning tools,
Region of interest,
Robust planning,
Scattering char-acteristics,
Sensor parameter,
User-friendly-software,
Synthetic aperture radar.
Abstract: A methodology was developed to assist in the planning of SAR acquisitions, supported by a user-friendly software. Using sensor parameters, the position and topography of the region of interest, and a proposed flight path, this planning tool simulates backscatter images, maps of scattering characteristics and image quality parameters such as the local incidence angle and the noise equivalent sigmaO. It produces flight and ground profiles and lists of key parameters. These outputs inform about expected SAR image characteristics and can be employed for optimization of the planning. Using this tool, a non-specialist can perform a robust planning of SAR acquisitions. @InProceedings{magnardWegmullerWernerBonvinMeierEUSAR2018SARPlanningTool, author = {Magnard, C. and Wegmuller, U. and Werner, C. and Bonvin, F. and Meier, E.}, booktitle = {Proc. European Conf. Synthetic Aperture Radar}, title = {Planning tool for {SAR} missions}, year = {2018}, pages = {1052-1057}, abstract = {A methodology was developed to assist in the planning of SAR acquisitions, supported by a user-friendly software. Using sensor parameters, the position and topography of the region of interest, and a proposed flight path, this planning tool simulates backscatter images, maps of scattering characteristics and image quality parameters such as the local incidence angle and the noise equivalent sigmaO. It produces flight and ground profiles and lists of key parameters. These outputs inform about expected SAR image characteristics and can be employed for optimization of the planning. Using this tool, a non-specialist can perform a robust planning of SAR acquisitions.}, isbn = {9783800746361}, issn = {21974403}, keywords = {Image segmentation; Optical variables measurement; Radar imaging, Image quality parameters; Incidence angles; Planning tools; Region of interest; Robust planning; Scattering char-acteristics; Sensor parameter; User-friendly-software, Synthetic aperture radar}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050505782&partnerID=40&md5=cc483818aff21c4d87e3e28fc76776aa}, } -
Muhammad Adnan Siddique,
Tazio Strozzi,
Irena Hajnsek,
and Othmar Frey.
A case study on the correction of atmosphere-induced phase disturbances for SAR tomography in mountainous areas.
In Proc. of EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar,
pages 1412-1416,
2018.
Keyword(s): SAR Processing,
SAR Tomography,
persistent scatterer interferometry,
PSI,
DInSAR,
multibaseline interferometry,
interferometric stacking,
deformation monitoring,
subsidence monitoring,
urban,
urban remote sensing,
buildings,
estimation,
remote sensing,
synthetic aperture radar,
thermal expansion,
tomography,
urban areas,
alpine,
rugged terrain,
atmospheric phase,
atmospheric phase screen,
APS,
mitigation of atmospheric phase,
turbulent atmospheric phase in alpine areas,
Cosmo-SkyMed,
Zermatt,
Mattertal,
Matter valley,
Switzerland,
multi-baseline interferometry.
Abstract: The estimation of the atmosphere-induced phase delay variations is often more involved in mountainous areas due to strong spatial variations of the local atmospheric conditions and propagation paths through the troposphere. Height dependent phase delay variation owing to vertical stratification of the atmosphere within the same range-azimuth resolution cell cannot be ignored. We propose a regression kriging-based data-driven method whereby phase corrections are applied for differential tomographic focusing at each 3D point of interest along the elevation axis. Experiments are performed on an interferometric stack comprising 32 Cosmo-SkyMed stripmap images acquired between 2008-2013 over the Matter Valley in the Swiss Alps. @InProceedings{siddiqueStrozziHajnsekFreyEUSAR2018PSITomoAlpineAtmoCaseStudy, author = {Siddique, Muhammad Adnan and Strozzi, Tazio and Hajnsek, Irena and Frey, Othmar}, booktitle = {Proc. of EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar}, title = {A case study on the correction of atmosphere-induced phase disturbances for {SAR} tomography in mountainous areas}, year = {2018}, pages = {1412--1416}, abstract = {The estimation of the atmosphere-induced phase delay variations is often more involved in mountainous areas due to strong spatial variations of the local atmospheric conditions and propagation paths through the troposphere. Height dependent phase delay variation owing to vertical stratification of the atmosphere within the same range-azimuth resolution cell cannot be ignored. We propose a regression kriging-based data-driven method whereby phase corrections are applied for differential tomographic focusing at each 3D point of interest along the elevation axis. Experiments are performed on an interferometric stack comprising 32 Cosmo-SkyMed stripmap images acquired between 2008-2013 over the Matter Valley in the Swiss Alps.}, file = {:siddiqueStrozziHajnsekFreyEUSAR2018PSITomoAlpineAtmoCaseStudy.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, alpine, rugged terrain, atmospheric phase, atmospheric phase screen, APS, mitigation of atmospheric phase, turbulent atmospheric phase in alpine areas, Cosmo-SkyMed, Zermatt, Mattertal, Matter valley, Switzerland, multi-baseline interferometry}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueStrozziHajnsekFreyEUSAR2018PSITomoAlpineAtmoCaseStudy.pdf}, } -
Muhammad A. Siddique,
Tazio Strozzi,
Irena Hajnsek,
and Othmar Frey.
SAR tomography for spatio-temporal inversion of coherent scatterers in villages of alpine regions.
In Proc. IEEE Int. Geosci. Remote Sens. Symp.,
pages 6099-6102,
2018.
Keyword(s): SAR Processing,
SAR Tomography,
persistent scatterer interferometry,
PSI,
DInSAR,
multibaseline interferometry,
interferometric stacking,
deformation monitoring,
subsidence monitoring,
urban,
urban remote sensing,
buildings,
estimation,
remote sensing,
synthetic aperture radar,
thermal expansion,
tomography,
urban areas,
alpine,
rugged terrain,
atmospheric phase,
atmospheric phase screen,
APS,
mitigation of atmospheric phase,
turbulent atmospheric phase in alpine areas,
Cosmo-SkyMed,
Zermatt,
Mattertal,
Matter valley,
Switzerland,
multi-baseline interferometry.
Abstract: Differential synthetic aperture radar (SAR) tomography allows separation of multiple coherent scatterers interfering in the same range-azimuth resolution cell as well as the estimation of the deformation parameters of each scatterer. In this way, the spatio-temporal tomographic inversion serves as a means to resolve the layover and simultaneously improve deformation sampling. Compared to metropolitan regions with several man-made structures, the prevalence of coherent scatterers in the villages of alpine regions is generally low, while at the same time layovers are widespread due to the ruggedness of the terrain. Moreover, the drastic height variations in the imaged scene necessitate height-dependent compensation of the atmospheric phase delay variations within the tomographic inversion. This paper addresses these concerns while performing experiments on an interferometric stack comprising 33 Cosmo-SkyMed strimap images acquired in the summers between 2008-13 over Matter Valley in the Swiss Alps. The results show improved deformation sampling along the layover-affected mountainside. @InProceedings{siddiqueStrozziHajnsekFreyIGARSS2018PSITomoAlpineAtmo, author = {Muhammad A. Siddique and Tazio Strozzi and Irena Hajnsek and Othmar Frey}, booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.}, title = {{SAR} tomography for spatio-temporal inversion of coherent scatterers in villages of alpine regions}, year = {2018}, pages = {6099--6102}, abstract = {Differential synthetic aperture radar (SAR) tomography allows separation of multiple coherent scatterers interfering in the same range-azimuth resolution cell as well as the estimation of the deformation parameters of each scatterer. In this way, the spatio-temporal tomographic inversion serves as a means to resolve the layover and simultaneously improve deformation sampling. Compared to metropolitan regions with several man-made structures, the prevalence of coherent scatterers in the villages of alpine regions is generally low, while at the same time layovers are widespread due to the ruggedness of the terrain. Moreover, the drastic height variations in the imaged scene necessitate height-dependent compensation of the atmospheric phase delay variations within the tomographic inversion. This paper addresses these concerns while performing experiments on an interferometric stack comprising 33 Cosmo-SkyMed strimap images acquired in the summers between 2008-13 over Matter Valley in the Swiss Alps. The results show improved deformation sampling along the layover-affected mountainside.}, doi = {10.1109/IGARSS.2018.8518296}, file = {:siddiqueStrozziHajnsekFreyIGARSS2018PSITomoAlpineAtmo.pdf:PDF}, keywords = {SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas, alpine, rugged terrain, atmospheric phase, atmospheric phase screen, APS, mitigation of atmospheric phase, turbulent atmospheric phase in alpine areas, Cosmo-SkyMed, Zermatt, Mattertal, Matter valley, Switzerland, multi-baseline interferometry}, owner = {ofrey}, pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueStrozziHajnsekFreyIGARSS2018PSITomoAlpineAtmo.pdf}, } -
F. Viviani,
A. Michelini,
L. Mayer,
and F. Conni.
IBIS-ArcSAR: an Innovative Ground-Based SAR System for Slope Monitoring.
In Proc. IEEE Int. Geosci. Remote Sens. Symp.,
pages 1348-1351,
July 2018.
Keyword(s): digital elevation models,
geomorphology,
geophysical equipment,
mining,
radar imaging,
radar interferometry,
synthetic aperture radar,
vertical height,
digital elevation model,
computationally fast interferometric processing algorithm,
simple fast interferometric processing algorithm,
Arc-scanning SAR systems,
2D SAR Image,
Multiple input Multiple Output,
MIMO Radar channels,
recent IBIS-ArcSAR product,
acquisition time,
IBIS-Rover product,
horizontal coverage,
IDS GeoRadar company,
IBIS-FM product,
elliptical shape,
azimuth coverage,
relevant limits,
open pit mines application,
open pit mines scenarios,
efficient tool,
GB-SAR,
decade Ground-Based SAR technology,
slope monitoring,
innovative ground-based SAR system,
time 1.0 min,
Synthetic aperture radar,
Azimuth,
Image reconstruction,
Monitoring,
Focusing,
Two dimensional displays,
Groun d-based Synthetic Aperture Radar,
Interferometry,
MIMO Radar,
Digital Elevation Models,
Radar Imaging.
Abstract: In the last decade Ground-Based SAR (GB-SAR) technology has been demonstrated to be one of the most efficient tool for slope monitoring in open pit mines scenarios. However, especially for open pit mines application, one of the relevant limits is the azimuth coverage, being the mine often of elliptical shape. In this context, the IBIS-FM product of IDS GeoRadar company can reach about 80deg of horizontal coverage, and can be overcome by IBIS-Rover product that can reach 270deg of horizontal coverage but increasing the acquisition time. The recent IBIS-ArcSAR product developed by IDS GeoRadar can overcome these limits, offering a full 360deg of horizontal coverage in less than 1 minute of acquisition time, with additional feature of a constant angular resolution. Moreover, by exploiting the new capability of MIMO (Multiple input Multiple Output) Radar channels, the vertical height or Digital Elevation Model (DEM) of the mine can be reconstructed through simple and computationally fast interferometric processing algorithms, together with an enhanced focusing of 2D SAR Image that is an open issue in Arc-scanning SAR systems. @InProceedings{vivianiEtalIGARSS2018IBISArcSAR, author = {F. {Viviani} and A. {Michelini} and L. {Mayer} and F. {Conni}}, booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.}, title = {{IBIS-ArcSAR}: an Innovative Ground-Based {SAR} System for Slope Monitoring}, year = {2018}, month = jul, pages = {1348-1351}, abstract = {In the last decade Ground-Based SAR (GB-SAR) technology has been demonstrated to be one of the most efficient tool for slope monitoring in open pit mines scenarios. However, especially for open pit mines application, one of the relevant limits is the azimuth coverage, being the mine often of elliptical shape. In this context, the IBIS-FM product of IDS GeoRadar company can reach about 80deg of horizontal coverage, and can be overcome by IBIS-Rover product that can reach 270deg of horizontal coverage but increasing the acquisition time. The recent IBIS-ArcSAR product developed by IDS GeoRadar can overcome these limits, offering a full 360deg of horizontal coverage in less than 1 minute of acquisition time, with additional feature of a constant angular resolution. Moreover, by exploiting the new capability of MIMO (Multiple input Multiple Output) Radar channels, the vertical height or Digital Elevation Model (DEM) of the mine can be reconstructed through simple and computationally fast interferometric processing algorithms, together with an enhanced focusing of 2D SAR Image that is an open issue in Arc-scanning SAR systems.}, doi = {10.1109/IGARSS.2018.8517702}, issn = {2153-7003}, keywords = {digital elevation models;geomorphology;geophysical equipment;mining;radar imaging;radar interferometry;synthetic aperture radar;vertical height;digital elevation model;computationally fast interferometric processing algorithm;simple fast interferometric processing algorithm;Arc-scanning SAR systems;2D SAR Image;Multiple input Multiple Output;MIMO Radar channels;recent IBIS-ArcSAR product;acquisition time;IBIS-Rover product;horizontal coverage;IDS GeoRadar company;IBIS-FM product;elliptical shape;azimuth coverage;relevant limits;open pit mines application;open pit mines scenarios;efficient tool;GB-SAR;decade Ground-Based SAR technology;slope monitoring;innovative ground-based SAR system;time 1.0 min;Synthetic aperture radar;Azimuth;Image reconstruction;Monitoring;Focusing;Two dimensional displays;Groun d-based Synthetic Aperture Radar;Interferometry;MIMO Radar;Digital Elevation Models;Radar Imaging}, owner = {ofrey}, } -
X. Xu,
C. A. Baldi,
J. De Bleser,
Y. Lei,
S. Yueh,
and D. Esteban-Fernandez.
Multi-Frequency Tomography Radar Observations of Snow Stratigraphy at Fraser During SnowEx.
In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium,
pages 6269-6272,
July 2018.
Keyword(s): CW radar,
FM radar,
geophysical signal processing,
hydrological techniques,
radar polarimetry,
radar signal processing,
remote sensing by radar,
snow,
signal processing algorithm,
snow free image,
snow density,
ground snow pit measurement,
radar design,
snow layer,
multiple viewing positions,
radar echo,
tomography technique,
radar channel,
three-dimensional variability,
fully polarimetric frequency-modulated continuous-wave radar,
triple-frequency,
2017 NASA SnowEx campaign,
Earth's terrestrial snow-covered regions,
multiyear airborne snow campaign,
Fraser,
snow stratigraphy,
multifrequency tomography radar observations,
frequency 17.2 GHz,
size 30.0 cm,
frequency 9.6 GHz,
frequency 13.5 GHz,
Snow,
Tomography,
Synthetic aperture radar,
Radar polarimetry,
Spaceborne radar,
Radar imaging,
tomography,
snow,
FMCW radar,
SWE.
Abstract: SnowEx is a multi-year airborne snow campaign led by NASA. The purpose of SnowEx is to figure out how much water is stored in Earth's terrestrial snow-covered regions. As part of the 2017 NASA SnowEx campaign, we deployed a portable triple-frequency (9.6GHz, 13.5GHz and 17.2GHz) and fully polarimetric frequency-modulated continuous-wave (FMCW) radar at Fraser, Colorado. The radar was installed on a 60cmx60cm frame to enable a full reconstruction of the three-dimensional variability per each radar channel. The tomography technique uses the radar echo from the multiple viewing positions and provides a unique access to the vertical structure of the snow layer. With current setup, the range resolution is 30cm. In this paper, we will review the radar design and signalprocessing algorithm - time domain back projection. The generated vertical images show the snow stratigraphy, which is consistent with ground snow pit measurement. The continuous operation demonstrates diurnal thawing and refreezing process. The snow density is retrieved by comparing to the snow free image. @InProceedings{xuBaldiDeBleserLeiYuehEstebanFernandezIGARSS2018TomographyRadarObservationsofSnowSnowEx, author = {X. {Xu} and C. A. {Baldi} and J. {De Bleser} and Y. {Lei} and S. {Yueh} and D. {Esteban-Fernandez}}, booktitle = {IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium}, title = {Multi-Frequency Tomography Radar Observations of Snow Stratigraphy at Fraser During SnowEx}, year = {2018}, month = {July}, pages = {6269-6272}, abstract = {SnowEx is a multi-year airborne snow campaign led by NASA. The purpose of SnowEx is to figure out how much water is stored in Earth's terrestrial snow-covered regions. As part of the 2017 NASA SnowEx campaign, we deployed a portable triple-frequency (9.6GHz, 13.5GHz and 17.2GHz) and fully polarimetric frequency-modulated continuous-wave (FMCW) radar at Fraser, Colorado. The radar was installed on a 60cmx60cm frame to enable a full reconstruction of the three-dimensional variability per each radar channel. The tomography technique uses the radar echo from the multiple viewing positions and provides a unique access to the vertical structure of the snow layer. With current setup, the range resolution is 30cm. In this paper, we will review the radar design and signalprocessing algorithm - time domain back projection. The generated vertical images show the snow stratigraphy, which is consistent with ground snow pit measurement. The continuous operation demonstrates diurnal thawing and refreezing process. The snow density is retrieved by comparing to the snow free image.}, doi = {10.1109/IGARSS.2018.8519538}, issn = {2153-7003}, keywords = {CW radar;FM radar;geophysical signal processing;hydrological techniques;radar polarimetry;radar signal processing;remote sensing by radar;snow;signal processing algorithm;snow free image;snow density;ground snow pit measurement;radar design;snow layer;multiple viewing positions;radar echo;tomography technique;radar channel;three-dimensional variability;fully polarimetric frequency-modulated continuous-wave radar;triple-frequency;2017 NASA SnowEx campaign;Earth's terrestrial snow-covered regions;multiyear airborne snow campaign;Fraser;snow stratigraphy;multifrequency tomography radar observations;frequency 17.2 GHz;size 30.0 cm;frequency 9.6 GHz;frequency 13.5 GHz;Snow;Tomography;Synthetic aperture radar;Radar polarimetry;Spaceborne radar;Radar imaging;tomography;snow;FMCW radar;SWE}, owner = {ofrey}, }
Internal reports
-
NISAR.
NASA-ISRO SAR (NISAR) Mission ScienceUsers' Handbook..
Technical report,
NASA Jet Propulsion Laboratory,
2018.
Keyword(s): L-band,
NASA,
ISRO,
NISAR,
spaceborne SAR,
SAR Interferometry,
deformation,
displacement,
ground motion,
geohazards,
sea ice types,
detection of icebergs,
forest,
monitoring,
changes in global forest carbon stocks,
carbon stocks,
Agriculture,
food security,
mapping of water availability,
water use,
soil moisture,
moisture,
glacier,
ice sheets,
climate change,
maritime surveillance.
Abstract: NISAR PROVIDESA MEANS OF DISENTANGLING AND CLARIFYING SPATIALLY AND TEMPORALLY COMPLEX PHENOMENA, RANGING FROM ECOSYSTEM DISTURBANCES, TO ICE SHEET COLLAPSE AND NATURAL HAZARDS INCLUDING EARTHQUAKES, TSUNAMIS, VOLCANOES, AND LANDSLIDES. NISAR WILL BE THE FIRST NASA RADAR MISSION TO SYSTEMATICALLY AND GLOBALLY STUDY SOLID EARTH, ICE MASSES, AND ECOSYSTEMS. The NASA-ISRO Synthetic Aperture Radar (SAR), or NISAR mission, is a multidisciplinary radar mission to make integrated measurements to understand the causes and consequences of land surface changes. NISAR will make global measurements of the causes and consequences of land surface changes for integration into Earth system models. NISAR provides a means of disentangling and clarifying spatially and temporally complex phenomena, ranging from ecosystem disturbances, to ice sheet collapse and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. The purpose of this handbook is to prepare scientists and algorithm developers for NISAR by providing a basic description of the mission and its data characteristics that will allow them to take full advantage of this comprehensive data set when it becomes available. NISAR is a joint partnership between the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organisation (ISRO). Since the 2007 National Academy of Science ''Decadal Survey'' report, ''Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond,'' NASA has been studying concepts for a Synthetic Aperture Radar mission to determine Earth change in three disciplines: ecosystems (vegetation and the carbon cycle), deformation (solid Earth studies), and cryospheric sciences (primarily as related to climatic drivers and effects on sea level). In the course of these studies, a partnership with ISRO developed, which led to a joint spaceborne mission with both L-band and S-band SAR systems onboard. The current 2018 Decadal Survey, ''Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space,'' confirms the importance of NISAR and encourages the international partnership between NASA and ISRO. The Earth Science Division (ESD) within the Science Mission Directorate (SMD) at NASA Headquarters has directed the Jet Propulsion Laboratory (JPL) to manage the United States component of the NISAR project. ESD has assigned the Earth Science Mission Program Office (ESMPO), located at Goddard Space Flight Center (GSFC), the responsibility for overall program management. The NISAR mission is derived from the Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) radar mission concept, which was one of the four Tier 1 missions recommended in the 2007 Decadal Survey. To satisfy requirements of three distinct scientific communities with global perspectives, as well as address the potentials of the system for new applications, the NISAR system comprises a dual frequency, fully polarimetric radar, with an imaging swath greater than 240 km. This design permits complete global coverage in a 12-day exact repeat to generate interferometric time series and perform systematic global mapping of the changing surface of the Earth. The recommended lidar component of DESDynI will be accomplished with the GEDI mission (Global Ecosystem Dynamics Investigation Lidar). NISAR's launch is planned for January 2022. After a 90-day commissioning period, the mission will conduct a minimum of three full years of science operations with the L-band SAR in a near-polar, dawn-dusk, frozen, sun-synchronous orbit to satisfy NASA's requirements; ISRO requires five years of operations with the S-band SAR. If the system does not use its fuel reserved excess capacity during the nominal mission, it is possible to extend mission operations further for either instrument. NISAR's science objectives are based on priorities identified in the 2007 Decadal Survey and rearticulated in the 2010 report on NASA's Climate-Centric Architecture. NISAR will be the first NASA radar mission to systematically and globally study solid Earth, ice masses, and ecosystems. NISAR will measure ice mass and land surface motions and changes, ecosystem disturbances, and biomass, elucidating underlying processes and improving fundamental scientific understanding. The measurements will improve forecasts and assessment of changing ecosystems, response of ice sheets, and natural hazards. NASA also supports use of the NISAR data for a broad range of applications that benefit society, including response to disasters around the world. In addition to the original NASA objectives, ISRO has identified a range of applications of particular relevance to India that the mission will address, including monitoring of agricultural biomass over India, monitoring and assessing disasters to which India responds, studying snow and glaciers in the Himalayas, and studying Indian coastal and near-shore oceans. All NISAR science data (L- and S-band) will be freely available and open to the public, consistent with the long-standing NASA Earth Science open data policy. With its global acquisition strategy, cloud-penetrating capability, high spatial resolution, and 12-day repeat pattern, NISAR will provide a reliable, spatially dense time series of radar data that will be a unique resource for exploring Earth change (Table 1-1). Anticipated scientific results over the course of the mission include: (1) Comprehensive assessment of motion along plate boundaries that cross land, identifying areas of increasing strain, and capturing signatures of several hundred earthquakes that will contribute to our understanding of fault systems; (2) Comprehensive inventories of global volcanoes, their state of activity and associated risks; (3) Comprehensive biomass assessment in low biomass areas where dynamics are greatest, and global disturbance assessments, agricultural change, and wetlands dynamics, informing carbon flux models at the most critical spatial and temporal scales; (4) In combination with GEDI and other missions, comprehensive global biomass to set the decadal boundary conditions for carbon flux models; (5) Complete assessments of the velocity state of Greenland's and Antarctica's ice sheets, each month over the mission life, as a key boundary condition for ice sheet models; (6) Regular monitoring of the world's most dynamic mountain glaciers; (7) Comprehensive mapping of sea ice motion and deformation, improving our understanding of ocean-atmosphere interaction at the poles; (8) A rich data set for exploring a broad range of applications that benefit from fast, reliable, and regular sampling of areas of interest on land or ice. These include infrastructure monitoring, agriculture and forestry, disaster response, aquifer utilization, and ship navigability. @TechReport{NISAR2018NISARMissionScienceUsersHandbook, author = {NISAR}, institution = {NASA Jet Propulsion Laboratory}, title = {NASA-ISRO SAR (NISAR) Mission ScienceUsers' Handbook.}, year = {2018}, abstract = {NISAR PROVIDESA MEANS OF DISENTANGLING AND CLARIFYING SPATIALLY AND TEMPORALLY COMPLEX PHENOMENA, RANGING FROM ECOSYSTEM DISTURBANCES, TO ICE SHEET COLLAPSE AND NATURAL HAZARDS INCLUDING EARTHQUAKES, TSUNAMIS, VOLCANOES, AND LANDSLIDES. NISAR WILL BE THE FIRST NASA RADAR MISSION TO SYSTEMATICALLY AND GLOBALLY STUDY SOLID EARTH, ICE MASSES, AND ECOSYSTEMS. The NASA-ISRO Synthetic Aperture Radar (SAR), or NISAR mission, is a multidisciplinary radar mission to make integrated measurements to understand the causes and consequences of land surface changes. NISAR will make global measurements of the causes and consequences of land surface changes for integration into Earth system models. NISAR provides a means of disentangling and clarifying spatially and temporally complex phenomena, ranging from ecosystem disturbances, to ice sheet collapse and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. The purpose of this handbook is to prepare scientists and algorithm developers for NISAR by providing a basic description of the mission and its data characteristics that will allow them to take full advantage of this comprehensive data set when it becomes available. NISAR is a joint partnership between the National Aeronautics and Space Administration (NASA) and the Indian Space Research Organisation (ISRO). Since the 2007 National Academy of Science ''Decadal Survey'' report, ''Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond,'' NASA has been studying concepts for a Synthetic Aperture Radar mission to determine Earth change in three disciplines: ecosystems (vegetation and the carbon cycle), deformation (solid Earth studies), and cryospheric sciences (primarily as related to climatic drivers and effects on sea level). In the course of these studies, a partnership with ISRO developed, which led to a joint spaceborne mission with both L-band and S-band SAR systems onboard. The current 2018 Decadal Survey, ''Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space,'' confirms the importance of NISAR and encourages the international partnership between NASA and ISRO. The Earth Science Division (ESD) within the Science Mission Directorate (SMD) at NASA Headquarters has directed the Jet Propulsion Laboratory (JPL) to manage the United States component of the NISAR project. ESD has assigned the Earth Science Mission Program Office (ESMPO), located at Goddard Space Flight Center (GSFC), the responsibility for overall program management. The NISAR mission is derived from the Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) radar mission concept, which was one of the four Tier 1 missions recommended in the 2007 Decadal Survey. To satisfy requirements of three distinct scientific communities with global perspectives, as well as address the potentials of the system for new applications, the NISAR system comprises a dual frequency, fully polarimetric radar, with an imaging swath greater than 240 km. This design permits complete global coverage in a 12-day exact repeat to generate interferometric time series and perform systematic global mapping of the changing surface of the Earth. The recommended lidar component of DESDynI will be accomplished with the GEDI mission (Global Ecosystem Dynamics Investigation Lidar). NISAR's launch is planned for January 2022. After a 90-day commissioning period, the mission will conduct a minimum of three full years of science operations with the L-band SAR in a near-polar, dawn-dusk, frozen, sun-synchronous orbit to satisfy NASA's requirements; ISRO requires five years of operations with the S-band SAR. If the system does not use its fuel reserved excess capacity during the nominal mission, it is possible to extend mission operations further for either instrument. NISAR's science objectives are based on priorities identified in the 2007 Decadal Survey and rearticulated in the 2010 report on NASA's Climate-Centric Architecture. NISAR will be the first NASA radar mission to systematically and globally study solid Earth, ice masses, and ecosystems. NISAR will measure ice mass and land surface motions and changes, ecosystem disturbances, and biomass, elucidating underlying processes and improving fundamental scientific understanding. The measurements will improve forecasts and assessment of changing ecosystems, response of ice sheets, and natural hazards. NASA also supports use of the NISAR data for a broad range of applications that benefit society, including response to disasters around the world. In addition to the original NASA objectives, ISRO has identified a range of applications of particular relevance to India that the mission will address, including monitoring of agricultural biomass over India, monitoring and assessing disasters to which India responds, studying snow and glaciers in the Himalayas, and studying Indian coastal and near-shore oceans. All NISAR science data (L- and S-band) will be freely available and open to the public, consistent with the long-standing NASA Earth Science open data policy. With its global acquisition strategy, cloud-penetrating capability, high spatial resolution, and 12-day repeat pattern, NISAR will provide a reliable, spatially dense time series of radar data that will be a unique resource for exploring Earth change (Table 1-1). Anticipated scientific results over the course of the mission include: (1) Comprehensive assessment of motion along plate boundaries that cross land, identifying areas of increasing strain, and capturing signatures of several hundred earthquakes that will contribute to our understanding of fault systems; (2) Comprehensive inventories of global volcanoes, their state of activity and associated risks; (3) Comprehensive biomass assessment in low biomass areas where dynamics are greatest, and global disturbance assessments, agricultural change, and wetlands dynamics, informing carbon flux models at the most critical spatial and temporal scales; (4) In combination with GEDI and other missions, comprehensive global biomass to set the decadal boundary conditions for carbon flux models; (5) Complete assessments of the velocity state of Greenland's and Antarctica's ice sheets, each month over the mission life, as a key boundary condition for ice sheet models; (6) Regular monitoring of the world's most dynamic mountain glaciers; (7) Comprehensive mapping of sea ice motion and deformation, improving our understanding of ocean-atmosphere interaction at the poles; (8) A rich data set for exploring a broad range of applications that benefit from fast, reliable, and regular sampling of areas of interest on land or ice. These include infrastructure monitoring, agriculture and forestry, disaster response, aquifer utilization, and ship navigability.}, file = {:NISAR2018NISARMissionScienceUsersHandbook.pdf:PDF}, keywords = {L-band, NASA, ISRO, NISAR, spaceborne SAR, SAR Interferometry, deformation, displacement, ground motion, geohazards, sea ice types, detection of icebergs, forest, monitoring, changes in global forest carbon stocks, carbon stocks, Agriculture, food security, mapping of water availability, water use, soil moisture, moisture, glacier, ice sheets, climate change, maritime surveillance}, owner = {ofrey}, }
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Last modified: Fri Feb 24 14:22:26 2023
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .
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