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Publications of year 1989

Thesis

  1. Jerald L. Bauck. Tomographic Processing of Synthetic Aperture Radar Signals for Enhanced Resolution. PhD thesis, 1989. Keyword(s): SAR Processing, Bistatic SAR, Back-Projection, bistatic synthetic aperture radar, Azimuth Focusing, convolution back-projection, elliptical-arc projections, final reconstructed image, ground patch, image resource, pixel, weighting, radar cross-sections, radar theory, Spotlight mode, Airborne SAR, Tomographic Processing, Tomography, Wavefront Curvature.
    Abstract: Spotlight-mode synthetic aperture radar imaging is studied from the viewpoint of tomographic signal processing which allows the relaxation of the nearly-universal assumption that plane waves pass over the ground patch. This allows high-quality image reconstruction in the face of arbitrary amounts of wavefront curvature such as would be present when the angle subtended by the ground patch, as seen by the radar,is not small. One such application is wide-area surveillance. A methodology is used which has the benefits of a wideband transmitted signal (impulse) and a sensible simulation. Image reconstruction algorithms are developed for monostatic and bistatic systems. Simulation results using these algorithms compare favorably with baseline simulations which use a more conventional algorithm operating on data which do not embody the effects of wavefront curvature. Comments on system design and computational implementation are made as necessary. A new set of problems which appear to benefit from the tomographic viewpoint is posed. This work may also find I applications in some forms of reflection tomography. 

    @PhdThesis{phDThesisBauck1989TomoBistaticSAR,
author = {Bauck, Jerald L.},
title = {Tomographic Processing of Synthetic Aperture Radar Signals for Enhanced Resolution},
year = {1989},
abstract = {Spotlight-mode synthetic aperture radar imaging is studied from the viewpoint of tomographic signal processing which allows the relaxation of the nearly-universal assumption that plane waves pass over the ground patch. This allows high-quality image reconstruction in the face of arbitrary amounts of wavefront curvature such as would be present when the angle subtended by the ground patch, as seen by the radar,is not small. One such application is wide-area surveillance. A methodology is used which has the benefits of a wideband transmitted signal (impulse) and a sensible simulation. Image reconstruction algorithms are developed for monostatic and bistatic systems. Simulation results using these algorithms compare favorably with baseline simulations which use a more conventional algorithm operating on data which do not embody the effects of wavefront curvature. Comments on system design and computational implementation are made as necessary. A new set of problems which appear to benefit from the tomographic viewpoint is posed. This work may also find I applications in some forms of reflection tomography.},
doi = {10.31224/osf.io/6a2tn},
file = {:phDThesisBauck1989TomoBistaticSAR.pdf:PDF},
institution = {University of Illinois at Urbana-Champaign},
keywords = {SAR Processing, Bistatic SAR, Back-Projection, bistatic synthetic aperture radar; Azimuth Focusing, convolution back-projection; elliptical-arc projections;final reconstructed image;ground patch;image resource;pixel;weighting;radar cross-sections;radar theory, Spotlight mode, Airborne SAR, Tomographic Processing, Tomography, Wavefront Curvature},
owner = {ofrey},
pdf = {../../../docs/phDThesisBauck1989TomoBistaticSAR.pdf},
url = {https://ntrl.ntis.gov/NTRL/},

}


Articles in journal or book chapters

  1. J. L. Bauck and W. K. Jenkins. Convolution-Backprojection Image Reconstruction For Bistatic Synthetic Aperture Radar With Correction For Wavefront Curvature And Propagation Attenuation. Proc.SPIE, 1101:1-8, 1989. Keyword(s): SAR Processing, Bistatic SAR, Back-Projection, bistatic synthetic aperture radar, Azimuth Focusing, convolution back-projection, elliptical-arc projections, final reconstructed image, ground patch, image resource, pixel, weighting, radar cross-sections, radar theory, Spotlight mode, Airborne SAR, Tomographic Processing, Tomography, Wavefront Curvature.
    Abstract: Signal processing for image reconstruction in synthetic aperture radar (SAR) historically has been based on Fourier transform techniques. One reason for this is the fact that, at the time when SAR was invented in the early 1950's and for some time after that, the only way to process the huge amounts of data in a reasonably expeditious manner was to use optical techniques, such processors being based, at least in part, on Fourier optical principles. With the advent of digital processing in recent years, the existence of efficient algorithms for the computation of the discrete Fourier transform has continued to offer compelling reasons to use Fourier-type inversion methods. Additionally, geometrically-related simplifications in most analyses have engendered the assumption of plane waves being present over the ground patch being imaged, again encouraging the use of Fourier techniques. In applications where the distance of the radar from the ground patch is very large compared to the size of the ground patch to be imaged, such processing is appropriate, though still an approximation. In other cases, the wavefront curvature cannot be ignored, and other steps must be taken in order to yield high-quality imagery. Recent investigations into the use of convolution-backprojection algorithms modified from computer-aided tomography have proved fruitful in correcting for wavefront curvature in monostatic SAR. This paper reports on similar success in bistatic SAR. There appear to be other applications that could benefit from other adaptations of the convolution-backprojection idea. 

    @Article{bauckJenkinsProcSPIE1989BistaticConvolutionBackprojection,
author = {Bauck, J. L. and Jenkins, W. K.},
journal = {Proc.SPIE},
title = {Convolution-Backprojection Image Reconstruction For Bistatic Synthetic Aperture Radar With Correction For Wavefront Curvature And Propagation Attenuation},
year = {1989},
pages = {1-8},
volume = {1101},
abstract = {Signal processing for image reconstruction in synthetic aperture radar (SAR) historically has been based on Fourier transform techniques. One reason for this is the fact that, at the time when SAR was invented in the early 1950's and for some time after that, the only way to process the huge amounts of data in a reasonably expeditious manner was to use optical techniques, such processors being based, at least in part, on Fourier optical principles. With the advent of digital processing in recent years, the existence of efficient algorithms for the computation of the discrete Fourier transform has continued to offer compelling reasons to use Fourier-type inversion methods. Additionally, geometrically-related simplifications in most analyses have engendered the assumption of plane waves being present over the ground patch being imaged, again encouraging the use of Fourier techniques. In applications where the distance of the radar from the ground patch is very large compared to the size of the ground patch to be imaged, such processing is appropriate, though still an approximation. In other cases, the wavefront curvature cannot be ignored, and other steps must be taken in order to yield high-quality imagery. Recent investigations into the use of convolution-backprojection algorithms modified from computer-aided tomography have proved fruitful in correcting for wavefront curvature in monostatic SAR. This paper reports on similar success in bistatic SAR. There appear to be other applications that could benefit from other adaptations of the convolution-backprojection idea.},
doi = {10.1117/12.960509},
file = {:bauckJenkinsProcSPIE1989BistaticConvolutionBackprojection.pdf:PDF},
keywords = {SAR Processing, Bistatic SAR, Back-Projection, bistatic synthetic aperture radar; Azimuth Focusing, convolution back-projection; elliptical-arc projections;final reconstructed image;ground patch;image resource;pixel;weighting;radar cross-sections;radar theory, Spotlight mode, Airborne SAR, Tomographic Processing, Tomography, Wavefront Curvature},
owner = {ofrey},
pdf = {../../../docs/bauckJenkinsProcSPIE1989BistaticConvolutionBackprojection.pdf},
url = {http://dx.doi.org/10.1117/12.960509},

}


  2. D. Blacknell, A. Freeman, S. Quegan, I.A. Ward, I.P. Finley, C.J. Oliver, R.G. White, and J.W. Wood. Geometric accuracy in airborne SAR images. Aerospace and Electronic Systems, IEEE Transactions on, 25(2):241-258, March 1989. Keyword(s): SAR Processing, Airborne SAR, Motion Compensation, Motion Errors, Residual Motion Errors, aircraft instrumentation, microwave imaging, position measurement, radar, X-band, airborne SAR images, autofocus, azimuth processing, azimuthal positioning accuracy, defocusing, geometric accuracy, range positioning accuracy, synthetic aperture radar.
    Abstract: Uncorrected across-track motions of a synthetic aperture radar (SAR) platform can cause both a severe loss of azimuthal positioning accuracy in, and defocusing of, the resultant SAR image. It is shown how the results of an autofocus procedure can be incorporated in the azimuth processing to produce a fully focused image that is geometrically accurate in azimuth. Range positioning accuracy is also discussed, leading to a comprehensive treatment of all aspects of geometric accuracy. The system considered is an X-band SAR 

    @Article{blacknellFreemanQueganWardFinleyOliverWhiteWood1989,
author = {Blacknell, D. and Freeman, A. and Quegan, S. and Ward, I.A. and Finley, I.P. and Oliver, C.J. and White, R.G. and Wood, J.W.},
journal = {Aerospace and Electronic Systems, IEEE Transactions on},
title = {{Geometric accuracy in airborne SAR images}},
year = {1989},
issn = {0018-9251},
month = {Mar},
number = {2},
pages = {241-258},
volume = {25},
abstract = {Uncorrected across-track motions of a synthetic aperture radar (SAR) platform can cause both a severe loss of azimuthal positioning accuracy in, and defocusing of, the resultant SAR image. It is shown how the results of an autofocus procedure can be incorporated in the azimuth processing to produce a fully focused image that is geometrically accurate in azimuth. Range positioning accuracy is also discussed, leading to a comprehensive treatment of all aspects of geometric accuracy. The system considered is an X-band SAR},
doi = {10.1109/7.18685},
file = {:blacknellFreemanQueganWardFinleyOliverWhiteWood1989.pdf:PDF},
keywords = {SAR Processing, Airborne SAR, Motion Compensation, Motion Errors, Residual Motion Errors, aircraft instrumentation, microwave imaging, position measurement, radar, X-band, airborne SAR images, autofocus, azimuth processing, azimuthal positioning accuracy, defocusing, geometric accuracy, range positioning accuracy, synthetic aperture radar},
pdf = {../../../docs/blacknellFreemanQueganWardFinleyOliverWhiteWood1989.pdf},
url = {http://ieeexplore.ieee.org/iel5/7/701/00018685.pdf},

}


  3. P. H. Eichel, D. C. Ghiglia, and C. V. Jakowatz. Speckle processing method for synthetic-aperture-radar phase correction. Opt. Lett., 14(1):1, 1989. Keyword(s): SAR Processing, Autofocus, Phase Gradient Autofocus, PGA.
    Abstract: Uncompensated phase errors present in synthetic-aperture-radar data can have a disastrous effect on reconstructed image quality. We present a new iterative algorithm that holds promise of being a robust estimator and corrector for arbitrary phase errors. Our algorithm is similar in many respects to speckle processing methods currently used in optical astronomy. We demonstrate its ability to focus scenes containing large amounts of phase error regardless of the phase-error structure or its source. The algorithm works extremely well in both high and low signal-to-clutter conditions without human intervention. 

    @Article{eichelGhigliaJakowatz1989:PGAutofocus,
Title = {Speckle processing method for synthetic-aperture-radar phase correction},
Author = {P. H. Eichel and D. C. Ghiglia and C. V. Jakowatz, Jr.},
Number = {1},
Pages = {1},
Url = {http://www.opticsinfobase.org/DirectPDFAccess/B56C8F98-BDB9-137E-C1C89153420D70A4_9494.pdf},
Volume = {14},
Year = {1989},
Abstract = {Uncompensated phase errors present in synthetic-aperture-radar data can have a disastrous effect on reconstructed image quality. We present a new iterative algorithm that holds promise of being a robust estimator and corrector for arbitrary phase errors. Our algorithm is similar in many respects to speckle processing methods currently used in optical astronomy. We demonstrate its ability to focus scenes containing large amounts of phase error regardless of the phase-error structure or its source. The algorithm works extremely well in both high and low signal-to-clutter conditions without human intervention.},
Journal = {Opt. Lett.},
Keywords = {SAR Processing, Autofocus, Phase Gradient Autofocus, PGA},
Pdf = {../../../docs/eichelGhigliaJakowatz1989.pdf},
Publisher = {OSA} 
}


  4. P. H. Eichel and C. V. Jakowatz. Phase-gradient algorithm as an optimal estimator of the phase derivative. Opt. Lett., 14(20):1101, 1989. Keyword(s): SAR Processing, Autofocus, Phase Gradient Autofocus, PGA.
    Abstract: The phase-gradient algorithm represents a powerful new signal-processing technique with applications to aperturesynthesis imaging. These include, for example, synthetic-aperture-radar phase correction and stellar-image reconstruction. The algorithm combines redundant information present in the data to arrive at an estimate of the phase derivative. We show that the estimator is in fact a linear, minimum-variance estimator of the phase derivative. 

    @Article{eichelJakowatz1989b:PGAutofocus,
Title = {Phase-gradient algorithm as an optimal estimator of the phase derivative},
Author = {P. H. Eichel and C. V. Jakowatz, Jr.},
Number = {20},
Pages = {1101},
Url = {http://www.opticsinfobase.org/DirectPDFAccess/B56BBC0E-BDB9-137E-C6FF2BB309852EF7_9826.pdf?},
Volume = {14},
Year = {1989},
Abstract = {The phase-gradient algorithm represents a powerful new signal-processing technique with applications to aperturesynthesis imaging. These include, for example, synthetic-aperture-radar phase correction and stellar-image reconstruction. The algorithm combines redundant information present in the data to arrive at an estimate of the phase derivative. We show that the estimator is in fact a linear, minimum-variance estimator of the phase derivative.},
Journal = {Opt. Lett.},
Keywords = {SAR Processing, Autofocus, Phase Gradient Autofocus, PGA},
Pdf = {../../../docs/eichelJakowatz1989b.pdf},
Publisher = {OSA} 
}


  5. Donald Fraser. Interpolation by the FFT Revisited - an Experimental Investigation. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37(5):665-675, May 1989. Keyword(s): Interpolation, Interpolation by FFT, Fast Fourier Transforms, FFT, Nyquist limit, RMS error, Sampling Rate Conversion, Upsampling, Sinusoidal Test Signal.
    Abstract: Interpolation by the FFT has become a practial proposition in many new areas, such as image resampling, with the recent emergence of extremly fast FFT and microcircuits. This paper desctibes a numerical investigation into the accuracy of interpolation by fast Fourier transform (FFT) using a sinusoidal test signal. The method is precisely defined, including a previously unnoticed detail which makes a significant difference to the accuracy of the result. The experiments show that, with no input windowing, the accuracy of interpolation is almost independent of sinusoidal wavelength very close to the Nyquist limit. The resulting RMS error is inversely proportional to input sequence length and is very low for sequence lengths likely to be encountered in practice. As wavelength passes through the Nyquist limit, there is a sudden increase in error, as is expected from sampling theory. If the sequence ends are windowed by short, cosine half-bells, accuracy is further improved at longer wavelengths. In comparison, small-kernel convolution methods, such as linear interpolation and cubic convolution, perform badly at wavelengths anywhere near the Nyquist limit 

    @Article{fraser89:Interpolation,
author = {Donald Fraser},
title = {{Interpolation by the FFT Revisited - an Experimental Investigation}},
journal = {IEEE Transactions on Acoustics, Speech, and Signal Processing},
year = {1989},
volume = {37},
number = {5},
pages = {665-675},
month = May,
abstract = {Interpolation by the FFT has become a practial proposition in many new areas, such as image resampling, with the recent emergence of extremly fast FFT and microcircuits. This paper desctibes a numerical investigation into the accuracy of interpolation by fast Fourier transform (FFT) using a sinusoidal test signal. The method is precisely defined, including a previously unnoticed detail which makes a significant difference to the accuracy of the result. The experiments show that, with no input windowing, the accuracy of interpolation is almost independent of sinusoidal wavelength very close to the Nyquist limit. The resulting RMS error is inversely proportional to input sequence length and is very low for sequence lengths likely to be encountered in practice. As wavelength passes through the Nyquist limit, there is a sudden increase in error, as is expected from sampling theory. If the sequence ends are windowed by short, cosine half-bells, accuracy is further improved at longer wavelengths. In comparison, small-kernel convolution methods, such as linear interpolation and cubic convolution, perform badly at wavelengths anywhere near the Nyquist limit},
file = {:fraser89.pdf:PDF},
keywords = {Interpolation, Interpolation by FFT, Fast Fourier Transforms, FFT, Nyquist limit, RMS error, Sampling Rate Conversion, Upsampling, Sinusoidal Test Signal},
pdf = {../../../docs/fraser89.pdf},
url = {http://ieeexplore.ieee.org/iel1/29/637/00017559.pdf},

}


  6. Andrew K. Gabriel, Richard M. Goldstein, and Howard A. Zebker. Mapping small elevation changes over large areas: Differential radar interferometry. Journal of Geophysical Research: Solid Earth, 94(B7):9183-9191, 1989. Keyword(s): Review Paper, SAR Processing, Interferometry, SAR Interferometry, differential SAR Interferometry, DInSAR, InSAR, deformation mapping, surface deformation, surface displacement, Topographic Mapping, Planetology: Solid Surface Planets and Satellites: Surfaces, Remote sensing, Radar astronomy.
    Abstract: A technique that uses synthetic aperture radar (SAR) images to measure very small (1 cm or less) surface motions with good resolution (10 m) over large swaths (50 km) is presented along with experimental results. The method could be used for accurate measurements of many geophysical phenomena, including swelling and buckling in fault zones, residual displacements from seismic events, and prevolcanic swelling. The method is based on SAR interferometry, where two images are made of a scene by simultaneously flying two physically separated antennas. Then the phases of corresponding pixels are differenced, and altitude formation is deduced from some simple computation and image rectification. It is also possible to use one antenna flown twice over the same scene; then, if the second flight exactly duplicates the track of the first, an interesting possibility occurs. There would be no phase changes between the images at all unless there was a physical change in the scene, such as ground swelling, that would alter the distance from some resolution element to the antenna. Since the phase changes all occur at the short carrier wavelength, the basic limitation on sensitivity is only the phase noise in the system. When the two imaging passes are made from flight tracks that are separated (which is the case with the Seasat images used here), it is no longer possible to distinguish surface changes from the parallax caused by topography. However, with some additional computation, a third image made at some other baseline may be used to remove the topography and leave only the surface changes. This method was applied using Seasat data to an imaging site in Imperial Valley, California, where motion effects were observed that were ascribed to the expansion of water-absorbing clays. Phase change images of this area are shown, along with associated ground truth about the presence of water. Problems with the technique are explored, along with a discussion of future experimental possibilities on upcoming SAR missions like Earth Observing System (EOS), Earth Resources Satellite (ERS 1), SIR-C, and the Venus imaging radar, Magellan. 

    @Article{gabrielGoldsteinZebkerJGRB1989DInSAR,
author = {Gabriel, Andrew K. and Goldstein, Richard M. and Zebker, Howard A.},
journal = {Journal of Geophysical Research: Solid Earth},
title = {Mapping small elevation changes over large areas: {D}ifferential radar interferometry},
year = {1989},
issn = {2156-2202},
number = {B7},
pages = {9183--9191},
volume = {94},
abstract = {A technique that uses synthetic aperture radar (SAR) images to measure very small (1 cm or less) surface motions with good resolution (10 m) over large swaths (50 km) is presented along with experimental results. The method could be used for accurate measurements of many geophysical phenomena, including swelling and buckling in fault zones, residual displacements from seismic events, and prevolcanic swelling. The method is based on SAR interferometry, where two images are made of a scene by simultaneously flying two physically separated antennas. Then the phases of corresponding pixels are differenced, and altitude formation is deduced from some simple computation and image rectification. It is also possible to use one antenna flown twice over the same scene; then, if the second flight exactly duplicates the track of the first, an interesting possibility occurs. There would be no phase changes between the images at all unless there was a physical change in the scene, such as ground swelling, that would alter the distance from some resolution element to the antenna. Since the phase changes all occur at the short carrier wavelength, the basic limitation on sensitivity is only the phase noise in the system. When the two imaging passes are made from flight tracks that are separated (which is the case with the Seasat images used here), it is no longer possible to distinguish surface changes from the parallax caused by topography. However, with some additional computation, a third image made at some other baseline may be used to remove the topography and leave only the surface changes. This method was applied using Seasat data to an imaging site in Imperial Valley, California, where motion effects were observed that were ascribed to the expansion of water-absorbing clays. Phase change images of this area are shown, along with associated ground truth about the presence of water. Problems with the technique are explored, along with a discussion of future experimental possibilities on upcoming SAR missions like Earth Observing System (EOS), Earth Resources Satellite (ERS 1), SIR-C, and the Venus imaging radar, Magellan.},
doi = {10.1029/JB094iB07p09183},
file = {:gabrielGoldsteinZebkerJGRB1989DInSAR.pdf:PDF},
keywords = {Review Paper, SAR Processing, Interferometry, SAR Interferometry, differential SAR Interferometry, DInSAR, InSAR, deformation mapping, surface deformation, surface displacement, Topographic Mapping, Planetology: Solid Surface Planets and Satellites: Surfaces, Remote sensing, Radar astronomy},
owner = {ofrey},
pdf = {../../../docs/gabrielGoldsteinZebkerJGRB1989DInSAR.pdf},
url = {http://dx.doi.org/10.1029/JB094iB07p09183},

}


  7. Dennis C. Ghiglia and Gary A. Mastin. Two-dimensional phase correction of synthetic-aperture-radar imagery. Opt. Lett., 14(20):1104-1106, October 1989. Keyword(s): SAR processing, Autofocus, Atmospheric turbulence, Coherent systems, Fourier transforms, Phase estimation, Point spread function, Speckle imaging.
    Abstract: A two-dimensional synthetic-aperture-radar (SAR) phase-correction algorithm is described as a natural extension of a one-dimensional technique developed previously. It embodies some similarities of phase-gradient speckle imaging and incorporates improvements in phase estimation. Diffraction-limited performance has been obtained on actual SAR imagery regardless of scene content or phase-error structure. The algorithm is computationally efficient, robust, and easily implemented on a general-purpose computer or special-purpose hardware. 

    @Article{ghigliaMastinOptLett1989TwoDimensionalPhaseCorrectionForSARAutofocus,
author = {Dennis C. Ghiglia and Gary A. Mastin},
journal = {Opt. Lett.},
title = {Two-dimensional phase correction of synthetic-aperture-radar imagery},
year = {1989},
month = {Oct},
number = {20},
pages = {1104--1106},
volume = {14},
abstract = {A two-dimensional synthetic-aperture-radar (SAR) phase-correction algorithm is described as a natural extension of a one-dimensional technique developed previously. It embodies some similarities of phase-gradient speckle imaging and incorporates improvements in phase estimation. Diffraction-limited performance has been obtained on actual SAR imagery regardless of scene content or phase-error structure. The algorithm is computationally efficient, robust, and easily implemented on a general-purpose computer or special-purpose hardware.},
doi = {10.1364/OL.14.001104},
keywords = {SAR processing, Autofocus, Atmospheric turbulence; Coherent systems; Fourier transforms; Phase estimation; Point spread function; Speckle imaging},
owner = {ofrey},
publisher = {OSA},
url = {http://ol.osa.org/abstract.cfm?URI=ol-14-20-1104},

}


  8. Soren N. Madsen. Estimating the Doppler Centroid of SAR Data. IEEE Transactions on Aerospace and Electronic Systems, 25(2):134-140, 1989. Keyword(s): SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Sign Doppler Estimator, SDE, Correlation Doppler Estimator, CDE, delta E Estimator, Satellite SAR, SEASAT.
    Abstract: After reviewing frequency-domain techniques for estimating the Doppler centroid of synthetic-aperture radar (SAR) data, the author describes a time-domain method and highlights its advantages. In particular, a nonlinear time-domain algorithm called the sign-Doppler estimator (SDE) is shown to have attractive properties. An evaluation based on an existing SEASAT processor is reported. The time-domain algorithms are shown to be extremely efficient with respect to requirements on calculations and memory, and hence they are well suited to real-time systems where the Doppler estimation is based on raw SAR data. For offline processors where the Doppler estimation is performed on processed data, which removes the problem of partial coverage of bright targets, the delta_E estimator and the CDE (correlation Doppler estimator) algorithm give similar performance. However, for nonhomogeneous scenes it is found that the nonlinear SDE algorithm, which estimates the Doppler-shift on the basis of data signs alone, gives superior performance. 

    @Article{madsen89:DopCentrEst,
Title = {{Estimating the Doppler Centroid of SAR Data}},
Author = {S{\o}ren N. Madsen},
Number = {2},
Pages = {134-140},
Url = {http://ieeexplore.ieee.org/iel5/7/701/00018675.pdf},
Volume = {25},
Year = {1989},
Abstract = {After reviewing frequency-domain techniques for estimating the Doppler centroid of synthetic-aperture radar (SAR) data, the author describes a time-domain method and highlights its advantages. In particular, a nonlinear time-domain algorithm called the sign-Doppler estimator (SDE) is shown to have attractive properties. An evaluation based on an existing SEASAT processor is reported. The time-domain algorithms are shown to be extremely efficient with respect to requirements on calculations and memory, and hence they are well suited to real-time systems where the Doppler estimation is based on raw SAR data. For offline processors where the Doppler estimation is performed on processed data, which removes the problem of partial coverage of bright targets, the delta_E estimator and the CDE (correlation Doppler estimator) algorithm give similar performance. However, for nonhomogeneous scenes it is found that the nonlinear SDE algorithm, which estimates the Doppler-shift on the basis of data signs alone, gives superior performance.},
Journal = {IEEE Transactions on Aerospace and Electronic Systems},
Keywords = {SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Sign Doppler Estimator, SDE, Correlation Doppler Estimator, CDE, delta E Estimator, Satellite SAR, SEASAT},
Pdf = {../../../docs/madsen89.pdf} 
}


  9. R.L. Mitchell. Creating complex signal samples from a band-limited real signal. Aerospace and Electronic Systems, IEEE Transactions on, 25(3):425-427, 1989. Keyword(s): quadrature demodulation, demodulation, digital filters, filtering and prediction theory, radar theory, signal processing, FIR filter, band-limited real signal, filter, finite-duration impulse response, image band rejection.
    Abstract: A very efficient method of creating complex signal samples from a band-limited real signal is presented. Because the method employs a simple mixer followed by one analog-to-digital (A/D) converter, plus a finite-duration impulse response (FIR) filter for image band rejection, there is no phase distortion in the resulting sampled signal. The method is more efficient than competing methods based on infinite-duration impulse response (IIR) filters. 

    @Article{mitchell89:demod,
author = {Mitchell, R.L.},
journal = {Aerospace and Electronic Systems, IEEE Transactions on},
title = {Creating complex signal samples from a band-limited real signal},
year = {1989},
number = {3},
pages = {425-427},
volume = {25},
abstract = {A very efficient method of creating complex signal samples from a band-limited real signal is presented. Because the method employs a simple mixer followed by one analog-to-digital (A/D) converter, plus a finite-duration impulse response (FIR) filter for image band rejection, there is no phase distortion in the resulting sampled signal. The method is more efficient than competing methods based on infinite-duration impulse response (IIR) filters.},
keywords = {quadrature demodulation, demodulation, digital filters, filtering and prediction theory, radar theory, signal processing, FIR filter, band-limited real signal, filter, finite-duration impulse response, image band rejection},
pdf = {data/sar44/ofrey/protected/PAPERS/mitchell89.pdf},
url = {http://ieeexplore.ieee.org/iel4/7/1324/00030799.pdf},

}


  10. 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: The authors derive the fundamental strip-mapping SAR (synthetic aperture radar) imaging equations from first principles. They show that the resolution mechanism relies on the geometry of the imaging situation rather than on the Doppler effect. Both the airborne and spaceborne cases are considered. Range processing is discussed by presenting an analysis of pulse compression and formulating a mathematical model of he radar return signal. This formulation is used to obtain the airborne SAR model. The authors study the resolution mechanism and derive the signal processing relations needed to produce a high-resolution image. They introduce spotlight-mode SAR and briefly indicate how polar-format spotlight processing can be used in strip-mapping SAR. They discuss a number of current and future research directions in SAR imaging 

    @Article{munsonVisentinTASS1989SignalProcViewStripMapSAR,
author = {Munson, David C. and Visentin, Robert L.},
title = {A signal processing view of strip-mapping synthetic aperture radar},
journal = {IEEE Transactions on Acoustics, Speech, and Signal Processing},
year = {1989},
volume = {37},
number = {12},
pages = {2131-2147},
month = dec,
issn = {0096-3518},
abstract = {The authors derive the fundamental strip-mapping SAR (synthetic aperture radar) imaging equations from first principles. They show that the resolution mechanism relies on the geometry of the imaging situation rather than on the Doppler effect. Both the airborne and spaceborne cases are considered. Range processing is discussed by presenting an analysis of pulse compression and formulating a mathematical model of he radar return signal. This formulation is used to obtain the airborne SAR model. The authors study the resolution mechanism and derive the signal processing relations needed to produce a high-resolution image. They introduce spotlight-mode SAR and briefly indicate how polar-format spotlight processing can be used in strip-mapping SAR. They discuss a number of current and future research directions in SAR imaging},
doi = {10.1109/29.45556},
file = {:munsonVisentinTASS1989SignalProcViewStripMapSAR.pdf:PDF},
keywords = {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},
owner = {ofrey},
pdf = {../../../docs/munsonVisentinTASS1989SignalProcViewStripMapSAR.pdf},

}


  11. Petre Stoica, Randolph L. Moses, Benjamin Friedlander, and Torsten Söderström. Maximum likelihood estimation of the parameters of multiple sinusoids from noisy measurements. Acoustics, Speech, and Signal Processing [see also IEEE Transactions on Signal Processing], IEEE Transactions on, 37(3):378-392, 1989. Keyword(s): RFI Suppression, filtering and prediction theory, spectral analysis, Cramer-Rao bound covariance matrix, initial estimates, maximum-likelihood, maximum-likelihood estimator, MLE, multiple sinusoids, noisy measurements.
    Abstract: The problem of estimating the frequencies, phases, and amplitudesof sinusoidal signals is considered. A simplified maximum-likelihoodGauss-Newton algorithm which provides asymptotically efficient estimatesof these parameters is proposed. Initial estimates for this algorithmare obtained by a variation of the overdetermined Yule-Walker method andperiodogram-based procedure. Use of the maximum-likelihood Gauss-Newtonalgorithm is not, however, limited to this particular initializationmethod. Some other possibilities to get suitable initial estimates arebriefly discussed. An analytical and numerical study of the shape of thelikelihood function associated with the sinusoids-in-noise processreveals its multimodal structure and clearly sets the importance of theinitialization procedure. Some numerical examples are presented toillustrate the performance of the proposed estimation procedure.Comparison to the performance corresponding to the Cramer-Rao lowerbound is also presented, using a simple expression for the asymptoticCramer-Rao bound covariance matrix derived in the paper 

    @Article{stoicaMosesFriedlanderSoederstroem89:RFI,
author = {Stoica, Petre and Moses, Randolph L. and Friedlander, Benjamin and S{\"o}derstr{\"o}m, Torsten},
journal = {Acoustics, Speech, and Signal Processing [see also IEEE Transactions on Signal Processing], IEEE Transactions on},
title = {{Maximum likelihood estimation of the parameters of multiple sinusoids from noisy measurements}},
year = {1989},
issn = {0096-3518},
number = {3},
pages = {378--392},
volume = {37},
abstract = {The problem of estimating the frequencies, phases, and amplitudesof sinusoidal signals is considered. A simplified maximum-likelihoodGauss-Newton algorithm which provides asymptotically efficient estimatesof these parameters is proposed. Initial estimates for this algorithmare obtained by a variation of the overdetermined Yule-Walker method andperiodogram-based procedure. Use of the maximum-likelihood Gauss-Newtonalgorithm is not, however, limited to this particular initializationmethod. Some other possibilities to get suitable initial estimates arebriefly discussed. An analytical and numerical study of the shape of thelikelihood function associated with the sinusoids-in-noise processreveals its multimodal structure and clearly sets the importance of theinitialization procedure. Some numerical examples are presented toillustrate the performance of the proposed estimation procedure.Comparison to the performance corresponding to the Cramer-Rao lowerbound is also presented, using a simple expression for the asymptoticCramer-Rao bound covariance matrix derived in the paper},
keywords = {RFI Suppression, filtering and prediction theory, spectral analysis, Cramer-Rao bound covariance matrix, initial estimates, maximum-likelihood, maximum-likelihood estimator, MLE, multiple sinusoids, noisy measurements},
owner = {ofrey},
pdf = {../../../docs/stoicaMosesFriedlanderSoederstroem89.pdf},
url = {http://ieeexplore.ieee.org/iel1/29/873/00021705.pdf},

}


  12. P. Stoica and Arye Nehorai. MUSIC, maximum likelihood, and Cramer-Rao bound. IEEE Transactions on Acoustics, Speech and Signal Processing, 37(5):720-741, May 1989. Keyword(s): SAR Processing, MUSIC, SAR Tomography, radio direction-finding, signal processing, Cramer-Rao bound, MUSIC estimator, covariance matrix, direction finding, maximum likelihood method, plane waves, statistical efficiency, uniform linear array.
    Abstract: The performance of the MUSIC and ML methods is studied, and their statistical efficiency is analyzed. The Cramer-Rao bound (CRB) for the estimation problems is derived, and some useful properties of the CRB covariance matrix are established. The relationship between the MUSIC and ML estimators is investigated as well. A numerical study is reported of the statistical efficiency of the MUSIC estimator for the problem of finding the directions of two plane waves using a uniform linear array. An exact description of the results is included 

    @Article{stoicaNehorai1989:MUSICMLCramerRao,
author = {Stoica, P. and Nehorai, Arye},
journal = {IEEE Transactions on Acoustics, Speech and Signal Processing},
title = {{MUSIC}, maximum likelihood, and Cramer-Rao bound},
year = {1989},
issn = {0096-3518},
month = {May},
number = {5},
pages = {720-741},
volume = {37},
abstract = {The performance of the MUSIC and ML methods is studied, and their statistical efficiency is analyzed. The Cramer-Rao bound (CRB) for the estimation problems is derived, and some useful properties of the CRB covariance matrix are established. The relationship between the MUSIC and ML estimators is investigated as well. A numerical study is reported of the statistical efficiency of the MUSIC estimator for the problem of finding the directions of two plane waves using a uniform linear array. An exact description of the results is included},
doi = {10.1109/29.17564},
keywords = {SAR Processing, MUSIC, SAR Tomography, radio direction-finding, signal processing, Cramer-Rao bound, MUSIC estimator, covariance matrix, direction finding, maximum likelihood method, plane waves, statistical efficiency, uniform linear array},
owner = {ofrey},
pdf = {../../../docs/stoicaNehorai1989.pdf},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=17564&isnumber=637},

}


  13. Jakob van Zyl. Unsupervised classification of scattering behavior using radar polarimetry data. IEEE Trans. Geosci. Remote Sens., 27(1):36-45, January 1989. Keyword(s): imaging radar polarimeter, land surface measurement, ocean, radar polarimetry, remote sensing technique, scattering behavior, unsupervised classification, urban, vegetation, electromagnetic wave polarisation, electromagnetic wave scattering, geophysical techniques, oceanographic techniques, radar applications, remote sensing;.
    Abstract: The use of an imaging radar polarimeter data for unsupervised classification of scattering behavior is described by comparing the polarization properties of each pixel in an image to that of simple classes of scattering such as even number of reflections, odd number of reflections, and diffuse scattering. For example, when this algorithm is applied to data acquired over the San Francisco Bay area in California, it classifies scattering by the ocean as being similar to that predicted by the class of odd number of reflections, scattering by the urban area as being similar to that predicted by the class of even number of reflections, and scattering by the Golden Gate Park as being similar to that predicted by the diffuse scattering class. It also classifies the scattering by a lighthouse in the ocean and boats on the ocean surface as being similar to that predicted by the even number of reflections class, making it easy to identify these objects against the background of the surrounding ocean 

    @Article{vanZyl1989,
author = {van Zyl, Jakob},
title = {Unsupervised classification of scattering behavior using radar polarimetry data},
journal = {IEEE Trans. Geosci. Remote Sens.},
year = {1989},
volume = {27},
number = {1},
pages = {36-45},
month = jan,
issn = {0196-2892},
abstract = {The use of an imaging radar polarimeter data for unsupervised classification of scattering behavior is described by comparing the polarization properties of each pixel in an image to that of simple classes of scattering such as even number of reflections, odd number of reflections, and diffuse scattering. For example, when this algorithm is applied to data acquired over the San Francisco Bay area in California, it classifies scattering by the ocean as being similar to that predicted by the class of odd number of reflections, scattering by the urban area as being similar to that predicted by the class of even number of reflections, and scattering by the Golden Gate Park as being similar to that predicted by the diffuse scattering class. It also classifies the scattering by a lighthouse in the ocean and boats on the ocean surface as being similar to that predicted by the even number of reflections class, making it easy to identify these objects against the background of the surrounding ocean},
doi = {10.1109/36.20273},
file = {:vanZyl1989.pdf:PDF},
keywords = {imaging radar polarimeter;land surface measurement;ocean;radar polarimetry;remote sensing technique;scattering behavior;unsupervised classification;urban;vegetation;electromagnetic wave polarisation;electromagnetic wave scattering;geophysical techniques;oceanographic techniques;radar applications;remote sensing;},
pdf = {../../../docs/vanZyl1989.pdf},

}


Conference articles

  1. J.L. Bauck and W. K. Jenkins. Convolution-backprojection image reconstruction for bistatic synthetic aperture radar. In Proc. IEEE Int. Symp. on Circuits and Systems, volume 3, pages 1512-1515, May 1989. Keyword(s): SAR Processing, Bistatic SAR, Back-Projection, bistatic synthetic aperture radar, Azimuth Focusing, convolution back-projection, elliptical-arc projections, final reconstructed image, ground patch, image resource, pixel, weighting, radar cross-sections, radar theory, Spotlight mode, Airborne SAR, Tomographic Processing, Tomography, Wavefront Curvature.
    Abstract: The algorithm presented accounts for the elliptical nature of the wavefronts over the ground patch (resulting in elliptical-arc projections) and is based on the convolution-backprojection (CBP) algorithm of computer tomography. Essentially, three changes were made to the CBP algorithm. First, instead of backprojection along straight lines, the backprojection is along the same elliptical arcs from which the data were taken. Second, each pixel in the image, during each backprojection, receives a weighting depending on its position in the image. Third, each projection receives an additional overall weighting depending on the positions of the transmitter and the receiver for the corresponding projection. As with CBP, each projection is convolved with a specified function before backprojection, and all of the backprojections are accumulated to form the final reconstructed image. 

    @InProceedings{BauckJenkins1989:BackProjectionBiStatic,
author = {Bauck, J.L. and Jenkins, W. K.},
booktitle = {Proc. IEEE Int. Symp. on Circuits and Systems},
title = {Convolution-backprojection image reconstruction for bistatic synthetic aperture radar},
year = {1989},
month = may,
pages = {1512-1515},
volume = {3},
abstract = {The algorithm presented accounts for the elliptical nature of the wavefronts over the ground patch (resulting in elliptical-arc projections) and is based on the convolution-backprojection (CBP) algorithm of computer tomography. Essentially, three changes were made to the CBP algorithm. First, instead of backprojection along straight lines, the backprojection is along the same elliptical arcs from which the data were taken. Second, each pixel in the image, during each backprojection, receives a weighting depending on its position in the image. Third, each projection receives an additional overall weighting depending on the positions of the transmitter and the receiver for the corresponding projection. As with CBP, each projection is convolved with a specified function before backprojection, and all of the backprojections are accumulated to form the final reconstructed image.},
doi = {10.1109/ISCAS.1989.100645},
keywords = {SAR Processing, Bistatic SAR, Back-Projection, bistatic synthetic aperture radar; Azimuth Focusing, convolution back-projection; elliptical-arc projections;final reconstructed image;ground patch;image resource;pixel;weighting;radar cross-sections;radar theory, Spotlight mode, Airborne SAR, Tomographic Processing, Tomography, Wavefront Curvature},

}


  2. C. Y. Chang and John C. Curlander. Doppler Centroid Estimation Ambiguity For Synthetic Aperture Radars. In IGARSS '89, International Geoscience and Remote Sensing Symposium, volume 4, pages 2567-2571, July 1989. Keyword(s): SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Doppler Ambiguity Resolver, DAR, Range Cross-Correlation Technique, Multiple PRF Technique, SIR-C.
    Abstract: A technique for estimation of the Doppler centroid of synthetic aperture radar (SAR) in the presence of a large antenna boresight pointing uncertainty is described. Also investigated is the image degradation resulting from data processing using an ambiguous centroid. Two approaches for Doppler centroid estimation (DCE) ambiguity resolution are presented: The range cross-correlation technique and the multiple PRF technique. For the multiple PRF technique, since other design factors control the selection for SAR, a generalized algorithm is derived for PRFs not containing a common divisor. An example using the Shuttle Imaging Radar (SIR-C) parameters illustrates that this algorithm is capable of resolving the C-band DCE ambiguity for antenna pointing uncertainties of 2? ~ 3?. 

    @InProceedings{ChanCurl89:Doppler,
Title = {{Doppler Centroid Estimation Ambiguity For Synthetic Aperture Radars}},
Author = {C. Y. Chang and John C. Curlander},
Booktitle = {IGARSS '89, International Geoscience and Remote Sensing Symposium},
Month = jul,
Pages = {2567-2571},
Volume = {4},
Year = {1989},
Abstract = {A technique for estimation of the Doppler centroid of synthetic aperture radar (SAR) in the presence of a large antenna boresight pointing uncertainty is described. Also investigated is the image degradation resulting from data processing using an ambiguous centroid. Two approaches for Doppler centroid estimation (DCE) ambiguity resolution are presented: The range cross-correlation technique and the multiple PRF technique. For the multiple PRF technique, since other design factors control the selection for SAR, a generalized algorithm is derived for PRFs not containing a common divisor. An example using the Shuttle Imaging Radar (SIR-C) parameters illustrates that this algorithm is capable of resolving the C-band DCE ambiguity for antenna pointing uncertainties of 2? ~ 3?.},
Keywords = {SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Doppler Ambiguity Resolver, DAR, Range Cross-Correlation Technique, Multiple PRF Technique, SIR-C},
Pdf = {../../../docs/changCurl89.pdf} 
}


  3. P.H. Eichel, D.C. Ghiglia, C.V. Jakowatz, G.A. Mastin, L.A. Romero, and D.E. Wahl. Applications of phase gradient autofocus to aperture synthesis imaging. In Multidimensional Signal Processing Workshop, 1989., Sixth, pages 57-58, Sept. 1989. Keyword(s): SAR Processing, Autofocus, Phase Gradient Autofocus. 
    @InProceedings{Eichel1989,
Title = {Applications of phase gradient autofocus to aperture synthesis imaging},
Author = {Eichel, P.H. and Ghiglia, D.C. and Jakowatz, C.V. and Mastin, G.A. and Romero, L.A. and Wahl, D.E.},
Booktitle = {Multidimensional Signal Processing Workshop, 1989., Sixth},
Month = {Sept.},
Pages = {57--58},
Year = {1989},
Keywords = {SAR Processing, Autofocus, Phase Gradient Autofocus},
Owner = {ofrey} 
}


  4. João Moreira and Winfried Poetzsch. Results Of The Real-time Adaptive Radiometric Correction Implemented In The Dfvlr L/C-band Sar. In Geoscience and Remote Sensing Symposium, 1989. IGARSS'89. 12th Canadian Symposium on Remote Sensing., 1989 International, volume 4, pages 2232-2234, 1989. Keyword(s): SAR Processing, AGC, Automatic Gain Control, STC, Sensitivity Time Control, Calibration, Radiometry, Radiometric Calibration, Radiometric Correction, APG, Antenna Gain Pattern, ESAR, E-SAR. 
    @InProceedings{moreiraPoetzsch89:AGCSTC,
Title = {Results Of The Real-time Adaptive Radiometric Correction Implemented In The Dfvlr L/C-band Sar},
Author = {Moreira, Jo{\~a}o and Poetzsch, Winfried},
Booktitle = {Geoscience and Remote Sensing Symposium, 1989. IGARSS'89. 12th Canadian Symposium on Remote Sensing., 1989 International},
Pages = {2232-2234},
Url = {http://ieeexplore.ieee.org/iel2/4280/12519/00577826.pdf},
Volume = {4},
Year = {1989},
Keywords = {SAR Processing, AGC, Automatic Gain Control, STC, Sensitivity Time Control, Calibration, Radiometry, Radiometric Calibration, Radiometric Correction, APG, Antenna Gain Pattern, ESAR, E-SAR},
Owner = {ofrey},
Pdf = {../../../docs/moreiraPoetzsch89.pdf} 
}


  5. R. Keith Raney and Paris W. Vachon. A Phase Preserving SAR Processor. In IGARSS '89, International Geoscience and Remote Sensing Symposium, volume 4, pages 2588-2591, July 1989. Keyword(s): SAR Processing, Phase Preserving, Range Migration Algorithm, omega-k, Wavenumber Domain Algorithm.
    Abstract: Synthetic aperture radar (SAR) image phase information is necessary to support many advanced SAR applications. The phase information in the complex image for conventional range-Doppler processors is not a robust estimate of scene phase. A SAR processor specifically designed to preserve phase information is being developed at the Canada Centre for Remote Sensing (CCRS). In addition to preserving vital phase information, this processor can support large degrees of range curvature and range migration. Therefore, it is possible, in principle, to use this processor for satellite SAR data, high resolution airborne SAR data, and for both squint mode and spotlight mode SAR data. This paper summarizes the theory and presents early results. 

    @InProceedings{raneyVachon89:PhasePreserving,
Title = {{A Phase Preserving SAR Processor}},
Author = {R. Keith Raney and Paris W. Vachon},
Booktitle = {IGARSS '89, International Geoscience and Remote Sensing Symposium},
Month = jul,
Pages = {2588-2591},
Volume = {4},
Year = {1989},
Abstract = {Synthetic aperture radar (SAR) image phase information is necessary to support many advanced SAR applications. The phase information in the complex image for conventional range-Doppler processors is not a robust estimate of scene phase. A SAR processor specifically designed to preserve phase information is being developed at the Canada Centre for Remote Sensing (CCRS). In addition to preserving vital phase information, this processor can support large degrees of range curvature and range migration. Therefore, it is possible, in principle, to use this processor for satellite SAR data, high resolution airborne SAR data, and for both squint mode and spotlight mode SAR data. This paper summarizes the theory and presents early results.},
Comment = {++},
Keywords = {SAR Processing, Phase Preserving, Range Migration Algorithm, omega-k, Wavenumber Domain Algorithm},
Pdf = {../../../docs/raney89.pdf} 
}


  6. Hartmut Runge and Richard Bamler. PRF Ambiguity Resolving for SAR. In IGARSS '89, International Geoscience and Remote Sensing Symposium, volume 4, pages 2572-2575, July 1989. Keyword(s): SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Doppler Ambiguity Resolver, DAR, Look Correlation, Comparison of Algorithms, SIR-C, X-SAR.
    Abstract: For high precision SAR (Synthetic Aperture Radar) processing, the determination of the absolute Doppler centroid is indispensable. The Doppler frequency estimated from azimuth spectra, however, suffers from the fact that the data are sampled with the PRF and an ambiguity about the correct PRF-band remains. Five methods for ambiguity resolving are proposed and discussed together with the already known technique of look correlation. None of these methods have a requirement on the mission schedule. It is shown that the following effect can be used to measure the absolute Doppler frequency: the Doppler shift of range spectra, range migration, image geometric misregistration and the use of multifrequency radar data. 

    @InProceedings{RungeBaml89:Doppler,
Title = {{PRF Ambiguity Resolving for SAR}},
Author = {Hartmut Runge and Richard Bamler},
Booktitle = {IGARSS '89, International Geoscience and Remote Sensing Symposium},
Month = jul,
Pages = {2572-2575},
Volume = {4},
Year = {1989},
Abstract = {For high precision SAR (Synthetic Aperture Radar) processing, the determination of the absolute Doppler centroid is indispensable. The Doppler frequency estimated from azimuth spectra, however, suffers from the fact that the data are sampled with the PRF and an ambiguity about the correct PRF-band remains. Five methods for ambiguity resolving are proposed and discussed together with the already known technique of look correlation. None of these methods have a requirement on the mission schedule. It is shown that the following effect can be used to measure the absolute Doppler frequency: the Doppler shift of range spectra, range migration, image geometric misregistration and the use of multifrequency radar data.},
Keywords = {SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Doppler Ambiguity Resolver, DAR, Look Correlation, Comparison of Algorithms, SIR-C, X-SAR},
Pdf = {../../../docs/rungeBamler89.pdf} 
}


  7. J. Siewerth. Theory And Quantitative Comparison Of Doppler Centroid Estimation Methods. In Geoscience and Remote Sensing Symposium, 1989. IGARSS'89. 12th Canadian Symposium on Remote Sensing. 1989 International, volume 4, pages 2576-2578, 1989. Keyword(s): SAR Processing, Doppler Centroid Estimation, Energy Balancing, Sign Doppler Estimator, SDE, Correlation Doppler Estimator, CDE, ERS.
    Abstract: The purpose of this paper is to describe the theory and implementation of three different Doppler centroid estimation methods and to present the first results of currently performed quantitative investigations. The Doppler centroid shift caused by the relative velocity between the sensor platform and the targets is derived by analysing the recieved SAR data. In contrast to the conventionally used Delta-E method (also called energy balancing), which is a frequency approach, the two other methods, the Correlation Doppler Estimator (CDE) and the Sign Doppler Estimator (SDE), are both performed in the time domain. 

    @InProceedings{siewerth89:dopCen,
Title = {Theory And Quantitative Comparison Of Doppler Centroid Estimation Methods},
Author = {Siewerth, J.},
Booktitle = {Geoscience and Remote Sensing Symposium, 1989. IGARSS'89. 12th Canadian Symposium on Remote Sensing. 1989 International},
Pages = {2576--2578},
Url = {http://ieeexplore.ieee.org/iel2/4280/12519/00577934.pdf},
Volume = {4},
Year = {1989},
Abstract = {The purpose of this paper is to describe the theory and implementation of three different Doppler centroid estimation methods and to present the first results of currently performed quantitative investigations. The Doppler centroid shift caused by the relative velocity between the sensor platform and the targets is derived by analysing the recieved SAR data. In contrast to the conventionally used Delta-E method (also called energy balancing), which is a frequency approach, the two other methods, the Correlation Doppler Estimator (CDE) and the Sign Doppler Estimator (SDE), are both performed in the time domain.},
Keywords = {SAR Processing, Doppler Centroid Estimation, Energy Balancing, Sign Doppler Estimator, SDE, Correlation Doppler Estimator, CDE, ERS},
Owner = {ofrey},
Pdf = {../../../docs/siewerth89.pdf} 
}


Internal reports

  1. Fabio Rocca, Claudio Prati, and Andrea Monti-Guarnieri. New Algorithms for Processing of SAR Data. ESA Contract Report, ESRIN Contract no. 7998/88/F/FL(SC), 1989. Keyword(s): SAR Processing, Range Migration Algorithm, omega-k, Wavenumber Domain Algorithm, Range-Doppler Algorithm, Secondary Range Compression, Comparison of Algorithms. 
    @TechReport{roccaPratiMontiGuarnieri89:omegak,
Title = {{New Algorithms for Processing of SAR Data}},
Author = {Fabio Rocca and Claudio Prati and Andrea Monti-Guarnieri},
Type = {ESA Contract Report, ESRIN Contract no. 7998/88/F/FL(SC)},
Year = {1989},
Keywords = {SAR Processing, Range Migration Algorithm, omega-k, Wavenumber Domain Algorithm, Range-Doppler Algorithm, Secondary Range Compression, Comparison of Algorithms} 
}


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Please note that access to full text PDF versions of papers is restricted to the Chair of Earth Observation and Remote Sensing, Institute of Environmental Engineering, ETH Zurich.
Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.

This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.



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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