Publications about 'Mathematical model'

Books and proceedings

1. Zhi-Hua Zhou. Machine Learning. Springer Singapore, 2021. Keyword(s): Machine Learning, Book on Machine Learning, Computer Science, Learning Algorithms, Neural Networks, Support Vector Machines, Decision Trees, Classification, Clustering, Supervised Learning, Semi-Supervised Learning, Unsupervised Learning, Metric Learning, Feature Selection, Rule Learning, Mathematical Models, Reinforcement Learning, Bayesian Networks, ML, AI, Artificial Intelligence. [Abstract] [bibtex-entry]

Thesis

1. S. Samie Esfahany. Exploitation of distributed scatterers in synthetic aperture radar interferometry. PhD thesis, TUDelft, 2017. [Abstract] [bibtex-entry]

Articles in journal or book chapters

1. S. T. Peters, D. M. Schroeder, M. S. Haynes, D. Castelletti, and A. Romero-Wolf. Passive Synthetic Aperture Radar Imaging Using Radio-Astronomical Sources. IEEE Trans. Geosci. Remote Sens., pp 1-16, 2021. Keyword(s): Synthetic aperture radar, Passive radar, Sun, Radar, Focusing, Signal to noise ratio, Mathematical model, Passive radar, passive radio sounding, passive synthetic aperture radar (SAR), radio echo sounding, Back-Projection, Time-Domain Back-Projection, TDBP. [Abstract] [bibtex-entry]



2. 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] [bibtex-entry]



3. 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] [bibtex-entry]



4. J. Pan, M. Durand, M. Sandells, J. Lemmetyinen, E. J. Kim, J. Pulliainen, A. Kontu, and C. Derksen. Differences Between the HUT Snow Emission Model and MEMLS and Their Effects on Brightness Temperature Simulation. IEEE Transactions on Geoscience and Remote Sensing, 54(4):2001-2019, April 2016. Keyword(s): radiative transfer, remote sensing, snow, HUT snow emission model, Helsinki University of Technology, brightness temperature simulation, snow water equivalent retrieval algorithm, passive microwave measurement, multiple-layer HUT model, Microwave Emission Model of Layered Snowpacks, scattered intensity, radiative transfer equation, one-flux equation, two-flux theory, HUT scattering coefficient, trapped-radiation, natural snow cover, Sodankyla, Finland, Churchill, Canada, Colorado, USA, snow grain size was, deep snow, Born approximation, root-mean-square error, Snow, Mathematical model, Scattering, Grain size, Microwave theory and techniques, Ice, Correlation, Model comparison, passive microwave remote sensing, snow, Model comparison, passive microwave remote sensing, snow. [Abstract] [bibtex-entry]



5. Zhu. Xiao Xiang and Richard Bamler. Superresolving SAR Tomography for Multidimensional Imaging of Urban Areas: Compressive sensing-based TomoSAR inversion. IEEE Signal Processing Magazine, 31(4):51-58, July 2014. Keyword(s): SAR Processing, SAR Tomography, PSI, Persistent Scatterer Interferometry, Deformation Monitoring, Deformation, compressed sensing, image motion analysis, image reconstruction, radar imaging, radar resolution, synthetic aperture radar, tomography, 4D point clouds, LiDAR, VHR spaceborne tomographic SAR inversion, building deformation, compressive sensing-based TomoSAR inversion, dynamic city model reconstruction, motion reconstruction, multicomponent nonlinear motion, multidimensional imaging, multiple scatterers, point density, shape reconstruction, synthetic aperture radar, urban areas, urban infrastructure, very high spatial resolution SAR tomography, Mathematical model, Signal processing algorithms, Signal resolution, Signal to noise ratio, Synthetic aperture radar, Tomography, Urban areas. [Abstract] [bibtex-entry]



6. Mariko S. Burgin, D. Clewley, R. M. Lucas, and Mahta Moghaddam. A Generalized Radar Backscattering Model Based on Wave Theory for Multilayer Multispecies Vegetation. IEEE Transactions on Geoscience and Remote Sensing, 49(12):4832-4845, December 2011. Keyword(s): backscatter, radar polarimetry, remote sensing by radar, vegetation, AIRSAR data, ALOS PALSAR, Advanced Land Observing Satellite, Airborne Synthetic Aperture Radar data, Australia, NASA JPL, NASA Jet Propulsion Laboratory, Phased Arrayed L-band Synthetic Aperture Radar data, Queensland, distorted Born approximation, generalized radar backscattering model, microwave interaction, multilayer multispecies vegetation, polarimetric radar backscattering coefficients, single species discrete scatterer model, soil moisture, structurally complex vegetation, surface model, surface roughness parameterization, two layer crown trunk models, wave theory, wooded savanna sites, Backscatter, Data models, Mathematical model, Scattering, Synthetic aperture radar, Vegetation, Forest scattering, multispecies vegetation, synthetic aperture radar (SAR) backscattering, wave theory. [Abstract] [bibtex-entry]



7. Guoxiang Liu, Hongguo Jia, Rui Zhang, Huixin Zhang, Hongliang Jia, Bing Yu, and Mingzhi Sang. Exploration of Subsidence Estimation by Persistent Scatterer InSAR on Time Series of High Resolution TerraSAR-X Images. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 4(1):159 -170, march 2011. Keyword(s): China, Jinghai County, Jinghu high-speed railway, Tianjin, X-band radar sensor, buildings, data reduction procedures, engineering risk assessment, ground subsidence, groundwater, high resolution TerraSAR-X images, in situ data, land use planning, manhole covers, persistent scatterer InSAR, radar line-of-sight direction, street lamps, subsidence estimation, time series, wavelength 3.1 cm, geomorphology, geophysical techniques, radar interferometry, remote sensing by radar, synthetic aperture radar;. [Abstract] [bibtex-entry]



8. T. O. Saebo, Roy E. Hansen, and A. Hanssen. Relative Height Estimation by Cross-Correlating Ground-Range Synthetic Aperture Sonar Images. IEEE Journal of Oceanic Engineering, 32(4):971-982, October 2007. Keyword(s): Synthetic Aperture Sonar, SAS, oceanographic techniques, seafloor phenomena, sonar imaging, synthetic aperture sonar, Elba Island, InSAS-2000 experiment, Italy, SAS processing, along-track resolution, azimuth resolution, broadband signals, coherent frequency-dependent scattering, correction technique, cross correlations, geometrical decorrelation effect, image acquisition, mathematical model, moving platform, seafloor relative height, signal-to-noise ratio, sonar images beamforming, synthetic aperture sonar imaging, time-delay estimates, vertically displaced receivers, Azimuth, Coherence, Decorrelation, Frequency estimation, Mathematical model, Scattering, Sea floor, Signal resolution, Signal to noise ratio, Synthetic aperture sonar, Bathymetry, coherence, cross correlation, height estimation, interferometry, synthetic aperture sonar (SAS), time-delay estimation. [Abstract] [bibtex-entry]



9. David C. Munson and Robert L. Visentin. A signal processing view of strip-mapping synthetic aperture radar. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37(12):2131-2147, December 1989. Keyword(s): SAR Processing, SAR Focusing, Azimuth Focusing, radar theory, signal processing, Doppler effect, SAR, airborne, imaging equations, polar-format, pulse compression, radar return signal, radar theory, signal processing, spaceborne, spotlight-mode, strip-mapping synthetic aperture radar, Doppler effect, Equations, Geometry, Image resolution, Pulse compression methods, Radar signal processing, Signal analysis, Signal resolution, Spaceborne radar, Synthetic aperture radar. [Abstract] [bibtex-entry]



10. Chialin Wu, K.Y. Liu, and M. Jin. Modeling and a Correlation Algorithm for Spaceborne SAR Signals. IEEE_J_AES, 18(5):563-575, September 1982. Keyword(s): SAR Processing, Range-Doppler Algorithm, RDA, Spaceborne SAR. [Abstract] [bibtex-entry]

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This collection of SAR literature is far from being complete.
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