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Publications of year 1999

Books and proceedings

  1. Mehrdad Soumekh. Synthetic Aperture Radar Signal Processing: with MATLAB Algorithms. John Wiley & Sons, 1999. Keyword(s): SAR Processing, Wavefront Reconstruction, Range Migration Algorithm, omega-k, Wavenumber Domain Algorithm, Back-Projection, Time-Domain Back-Projection, TDBP, Spotlight SAR, Stripmap SAR, MATLAB, Motion Compensation, Digital Spotlighting, Monopulse SAR, Stolt Mapping, Range Compression, Pulse Compression, Pulse Compression of Linear FM Signals, Linear FM Signals.
    Abstract: This book introduces the wavefront reconstruction signal theory that underlies the best SAR imaging methods and provides clear guidelines to system design, implementation, and applications in diverse areas - from airborne reconnaissance to topographic imaging of ocean floors to surveillance and air traffic control to medical imaging techniques, and numerous others. Enabling professionals in radar signal and image processing to use synthetic aperture technology to its fullest potential, this work: includes M-files to supplement this book; provides practical examples and results from real SAR, ISAR, and CSAR databases; outlines unique properties of the SAR signal that cannot be found in other information processing systems; examines spotlight SAR, stripmap SAR, circular SAR, and monopulse SAR modalities; discusses classical SAR processing issues such as motion compensation and radar calibration.

    @Book{soumekh:SARProc,
    Title = {{Synthetic Aperture Radar Signal Processing: with MATLAB Algorithms}},
    Author = {Mehrdad Soumekh},
    Publisher = {John Wiley \& Sons},
    Year = {1999},
    Abstract = {This book introduces the wavefront reconstruction signal theory that underlies the best SAR imaging methods and provides clear guidelines to system design, implementation, and applications in diverse areas - from airborne reconnaissance to topographic imaging of ocean floors to surveillance and air traffic control to medical imaging techniques, and numerous others. Enabling professionals in radar signal and image processing to use synthetic aperture technology to its fullest potential, this work: includes M-files to supplement this book; provides practical examples and results from real SAR, ISAR, and CSAR databases; outlines unique properties of the SAR signal that cannot be found in other information processing systems; examines spotlight SAR, stripmap SAR, circular SAR, and monopulse SAR modalities; discusses classical SAR processing issues such as motion compensation and radar calibration.},
    Keywords = {SAR Processing, Wavefront Reconstruction, Range Migration Algorithm, omega-k, Wavenumber Domain Algorithm, Back-Projection, Time-Domain Back-Projection, TDBP, Spotlight SAR, Stripmap SAR, MATLAB, Motion Compensation, Digital Spotlighting, Monopulse SAR, Stolt Mapping,Range Compression, Pulse Compression, Pulse Compression of Linear FM Signals, Linear FM Signals} 
    }
    


Articles in journal or book chapters

  1. S. Albrecht and I. Cumming. Application of momentary Fourier transform to SAR processing. IEE Proceedings - Radar, Sonar and Navigation, 146(6):285-297, December 1999. Keyword(s): SAR Processing, SPECAN, Modified SPECAN, discrete Fourier transforms, fast Fourier transforms, inverse problems, radar signal processing, synthetic aperture radar, DFT, FFT/IFFT algorithms, IDFT, SAR processing, SIFFT method, general matrix transforms, image processing, inverse momentary Fourier transform, momentary Fourier transform, MFT, recursive momentary Fourier transform, signal processing, synthetic aperture radar, windowing.
    Abstract: A common technique in signal and image processing is to extract a portion of the signal by windowing, and then perform the DFT on the window contents. The momentary Fourier transform (MFT) applies to the particular case where the window is moved one data sample along the signal between successive transforms. An alternative derivation of the recursive form of the MFT using general matrix transforms is given. How DFTs and IDFTs are used in the SPECAN (spectral analysis) and SIFFT (short IFFT) methods of synthetic aperture radar (SAR) processing is described. The MFT and inverse MFT are applied to those methods and the advantages and disadvantages they have compared to the FFT/IFFT algorithms are shown

    @Article{albrechtCumming1999:MFTSPECAN,
    Title = {Application of momentary {F}ourier transform to {SAR} processing},
    Author = {Albrecht, S. and Cumming, I.},
    Doi = {10.1049/ip-rsn:19990777},
    ISSN = {1350-2395},
    Month = dec,
    Number = {6},
    Pages = {285-297},
    Url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=822086&isnumber=17798},
    Volume = {146},
    Year = {1999},
    Abstract = {A common technique in signal and image processing is to extract a portion of the signal by windowing, and then perform the DFT on the window contents. The momentary Fourier transform (MFT) applies to the particular case where the window is moved one data sample along the signal between successive transforms. An alternative derivation of the recursive form of the MFT using general matrix transforms is given. How DFTs and IDFTs are used in the SPECAN (spectral analysis) and SIFFT (short IFFT) methods of synthetic aperture radar (SAR) processing is described. The MFT and inverse MFT are applied to those methods and the advantages and disadvantages they have compared to the FFT/IFFT algorithms are shown},
    Journal = {IEE Proceedings - Radar, Sonar and Navigation},
    Keywords = {SAR Processing, SPECAN, Modified SPECAN, discrete Fourier transforms, fast Fourier transforms, inverse problems, radar signal processing, synthetic aperture radar, DFT, FFT/IFFT algorithms, IDFT, SAR processing, SIFFT method, general matrix transforms, image processing, inverse momentary Fourier transform, momentary Fourier transform, MFT, recursive momentary Fourier transform, signal processing, synthetic aperture radar, windowing},
    Owner = {ofrey},
    Pdf = {../../../docs/albrechtCumming1999.pdf} 
    }
    


  2. S.R. Cloude, J. Fortuny, J.M. Lopez-Sanchez, and A.J. Sieber. Wide-band polarimetric radar inversion studies for vegetation layers. IEEE Transactions on Geoscience and Remote Sensing, 37(5):2430-2441, September 1999. Keyword(s): backscatter, forestry, geophysical techniques, image classification, radar cross-sections, radar polarimetry, remote sensing by radar, synthetic aperture radar, vegetation mappingbackscatter, canopy, complex volume scattering, entropy-alpha target decomposition scheme, ficus tree, fig, fir tree, forest, forestry, geophysical measurement technique, image classification scheme, inversion algorithm, parametric inversion, polarimetric radar inversion, radar polarimetry, radar scattering, radar theory, random particle cloud model, small anisotropic particles, two-parameter model, vegetation layer, vegetation mapping, wide band method.
    Abstract: The authors show how the entropy-alpha target decomposition scheme may be used for parametric inversion studies on random particle cloud models for vegetation layers. The decomposition is detailed first and then applied to a two-parameter model for backscatter from a random cloud of small anisotropic particles. The two main parameters used are the mean particle shape and the mean orientation angle of the cloud. An inversion algorithm is presented and applied to broad-band polarimetric radar data from the European Microwave Signature Laboratory (EMSL), Joint Research Center, Ispra, Italy. The results have been obtained from measurements of a fir tree and a ficus tree. They show a wavelength scale dependence of the shape and distribution of scatterers, which reflects the complex volume scattering nature of such problems. Moreover, the values and trends from these two trees as a function of the frequency are different, as expected from their physical structures. Consequently, this algorithm has the potential to be useful in the construction of classification schemes for vegetation

    @Article{cloudeFortunyLopezSanchezSieber1999:PolSARDecompVegetatioInversion,
    Title = {Wide-band polarimetric radar inversion studies for vegetation layers},
    Author = {Cloude, S.R. and Fortuny, J. and Lopez-Sanchez, J.M. and Sieber, A.J.},
    Doi = {10.1109/36.789640},
    ISSN = {0196-2892},
    Month = sep,
    Number = {5},
    Pages = {2430-2441},
    Url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=789640&isnumber=17111&tag=1},
    Volume = {37},
    Year = {1999},
    Abstract = {The authors show how the entropy-alpha target decomposition scheme may be used for parametric inversion studies on random particle cloud models for vegetation layers. The decomposition is detailed first and then applied to a two-parameter model for backscatter from a random cloud of small anisotropic particles. The two main parameters used are the mean particle shape and the mean orientation angle of the cloud. An inversion algorithm is presented and applied to broad-band polarimetric radar data from the European Microwave Signature Laboratory (EMSL), Joint Research Center, Ispra, Italy. The results have been obtained from measurements of a fir tree and a ficus tree. They show a wavelength scale dependence of the shape and distribution of scatterers, which reflects the complex volume scattering nature of such problems. Moreover, the values and trends from these two trees as a function of the frequency are different, as expected from their physical structures. Consequently, this algorithm has the potential to be useful in the construction of classification schemes for vegetation},
    Journal = {IEEE Transactions on Geoscience and Remote Sensing},
    Keywords = {backscatter, forestry, geophysical techniques, image classification, radar cross-sections, radar polarimetry, remote sensing by radar, synthetic aperture radar, vegetation mappingbackscatter, canopy, complex volume scattering, entropy-alpha target decomposition scheme, ficus tree, fig, fir tree, forest, forestry, geophysical measurement technique, image classification scheme, inversion algorithm, parametric inversion, polarimetric radar inversion, radar polarimetry, radar scattering, radar theory, random particle cloud model, small anisotropic particles, two-parameter model, vegetation layer, vegetation mapping, wide band method},
    Owner = {ofrey},
    Pdf = {../../../docs/cloudeFortunyLopezSanchezSieber1999.pdf} 
    }
    


  3. D.L. Evans. Applications of imaging radar data in Earth science investigations. Electronics Communication Engineering Journal, 11(5):227 -234, October 1999. Keyword(s): Earth science investigations, Earth's surface, LightSAR mission, SAR interferometric measurements, biodiversity, biomass, fine resolution, forest regrowth, glacier ice velocity measurement, imaging radar data, interferometric data acquisition, land cover, large-scale surface change, long-term observations, natural hazards, polarimetric data acquisition, receive polarisation, resource assessment, scatterer cross-sections, spaceborne SAR systems, surface topographic change monitoring, synthetic aperture radar, topographic data sets, transmit polarisation, vegetation, data acquisition, electromagnetic wave scattering, health hazards, image resolution, radar applications, radar cross-sections, radar imaging, radar polarimetry, radar resolution, radiowave interferometry, remote sensing by radar, spaceborne radar, synthetic aperture radar, topography (Earth);.
    Abstract: Synthetic aperture radar (SAR) data provide unique information about the Earth's surface and biodiversity, including critical data for natural hazards and resource assessments. The ability to calculate the cross-section of a scatterer for any transmit and receive polarisation combination provides detailed information about vegetation for assessing changes in land cover, biomass and forest regrowth. Unique SAR interferometric measurements, predominantly large-scale surface change at fine resolution, are used to generate topographic data sets, monitor surface topographic change, and measure glacier ice velocity. The LightSAR mission, planned for launch in 2002 will be optimised for polarimetric and interferometric data acquisition in order to provide long-term observations of the Earth's changing conditions

    @Article{810214,
    author = {Evans, D.L.},
    journal = {Electronics Communication Engineering Journal},
    title = {Applications of imaging radar data in Earth science investigations},
    year = {1999},
    issn = {0954-0695},
    month = {oct},
    number = {5},
    pages = {227 -234},
    volume = {11},
    abstract = {Synthetic aperture radar (SAR) data provide unique information about the Earth's surface and biodiversity, including critical data for natural hazards and resource assessments. The ability to calculate the cross-section of a scatterer for any transmit and receive polarisation combination provides detailed information about vegetation for assessing changes in land cover, biomass and forest regrowth. Unique SAR interferometric measurements, predominantly large-scale surface change at fine resolution, are used to generate topographic data sets, monitor surface topographic change, and measure glacier ice velocity. The LightSAR mission, planned for launch in 2002 will be optimised for polarimetric and interferometric data acquisition in order to provide long-term observations of the Earth's changing conditions},
    doi = {10.1049/ecej:19990504},
    keywords = {Earth science investigations;Earth's surface;LightSAR mission;SAR interferometric measurements;biodiversity;biomass;fine resolution;forest regrowth;glacier ice velocity measurement;imaging radar data;interferometric data acquisition;land cover;large-scale surface change;long-term observations;natural hazards;polarimetric data acquisition;receive polarisation;resource assessment;scatterer cross-sections;spaceborne SAR systems;surface topographic change monitoring;synthetic aperture radar;topographic data sets;transmit polarisation;vegetation;data acquisition;electromagnetic wave scattering;health hazards;image resolution;radar applications;radar cross-sections;radar imaging;radar polarimetry;radar resolution;radiowave interferometry;remote sensing by radar;spaceborne radar;synthetic aperture radar;topography (Earth);},
    
    }
    


  4. Gianfranco Fornaro. Trajectory Deviations in Airborne SAR: Analysis and Compensation. IEEE Transactions on Aerospace and Electronic Systems, 35(3):997-1009, July 1999. Keyword(s): SAR Processing, Motion Compensation, Airborne SAR, Residual Motion Errors, Non-Linear Flight Path, Non-linear SAR.
    Abstract: This paper concerns the analysis and compensation of trajectory deviations in airborne synthetic aperture radar (SAR) systems. Analysis of the received data spectrum is carried out with respect to the system geometry in the presence of linear, sinusoidal, and general aircraft displacements. This shows trajectory deviations generally produce spectral replicas along the azimuth frequency that strongly impair the quality of the focused image. Based on the derived model, we explain the rationale of the motion compensation (MOCO) strategy that must be applied at the SAR processing stage in order to limit the resolution loss. To this end aberration terms are separated into range space invariant and variant components. The former can be accounted for either in a preprocessing step or efficiently at range compression stage. The latter needs a prior accommodation of range migration effect. We design the procedure for efficient inclusion of the MOCO within a high precision Scaled FT based SAR processing algorithm. Finally, we present results on simulated data aimed at validating the whole analysis and the proposed procedure.

    @Article{fornaroTGRS1999TrajectoryDeviationsAirborneSAR,
    author = {Gianfranco Fornaro},
    journal = {IEEE Transactions on Aerospace and Electronic Systems},
    title = {Trajectory Deviations in Airborne {SAR}: Analysis and Compensation},
    year = {1999},
    month = jul,
    number = {3},
    pages = {997--1009},
    volume = {35},
    abstract = {This paper concerns the analysis and compensation of trajectory deviations in airborne synthetic aperture radar (SAR) systems. Analysis of the received data spectrum is carried out with respect to the system geometry in the presence of linear, sinusoidal, and general aircraft displacements. This shows trajectory deviations generally produce spectral replicas along the azimuth frequency that strongly impair the quality of the focused image. Based on the derived model, we explain the rationale of the motion compensation (MOCO) strategy that must be applied at the SAR processing stage in order to limit the resolution loss. To this end aberration terms are separated into range space invariant and variant components. The former can be accounted for either in a preprocessing step or efficiently at range compression stage. The latter needs a prior accommodation of range migration effect. We design the procedure for efficient inclusion of the MOCO within a high precision Scaled FT based SAR processing algorithm. Finally, we present results on simulated data aimed at validating the whole analysis and the proposed procedure.},
    file = {:fornaroTGRS1999TrajectoryDeviationsAirborneSAR.pdf:PDF},
    keywords = {SAR Processing, Motion Compensation, Airborne SAR, Residual Motion Errors, Non-Linear Flight Path, Non-linear SAR},
    owner = {ofrey},
    pdf = {../../../docs/fornaro1999.pdf},
    url = {http://ieeexplore.ieee.org/iel5/7/17004/00784069.pdf},
    
    }
    


  5. G. Fornaro and E. Sansosti. A two-dimensional region growing least squares phase unwrapping algorithm for interferometric SAR processing. IEEE Transactions on Geoscience and Remote Sensing, 37(5):2215 -2226, September 1999. Keyword(s): 2-D phase unwrapping algorithm, boundary phase values, discrete domain case, finite element method, interferometric SAR processing, reconstructed phase, two-dimensional region growing least squares phase unwrapping algorithm, wrapped phase image, geophysical signal processing, least squares approximations, radar imaging, radiowave interferometry, remote sensing by radar, synthetic aperture radar.
    Abstract: This paper presents a new two-dimensional (2-D) phase unwrapping (PhU) algorithm based on a least squares (LS) region growing strategy: the wrapped phase image is partitioned in different regions that are sequentially unwrapped via a LS algorithm. Reliable regions are dealt with at the beginning of the procedure, while critical areas are unwrapped in the final steps, thus avoiding error propagation from critical to reliable areas. A conditioned least squares formulation of the phase unwrapping problem is the core of the proposed procedure: this allows the solution to be tied to ldquo;some rdquo; known boundary phase values, thus guaranteeing the correct joining of the reconstructed phase in between the different regions and preventing them from being independently unwrapped. The application of the finite element method allows a straightforward implementation of the algorithm in the discrete domain case. Experimental results, carried out on simulated and real interferometric SAR data, show the effectiveness of the proposed algorithm and the improved performances with respect to existing unwrapping procedures

    @Article{789618,
    Title = {A two-dimensional region growing least squares phase unwrapping algorithm for interferometric SAR processing},
    Author = {Fornaro, G. and Sansosti, E.},
    Doi = {10.1109/36.789618},
    ISSN = {0196-2892},
    Month = sep,
    Number = {5},
    Pages = {2215 -2226},
    Volume = {37},
    Year = {1999},
    Abstract = {This paper presents a new two-dimensional (2-D) phase unwrapping (PhU) algorithm based on a least squares (LS) region growing strategy: the wrapped phase image is partitioned in different regions that are sequentially unwrapped via a LS algorithm. Reliable regions are dealt with at the beginning of the procedure, while critical areas are unwrapped in the final steps, thus avoiding error propagation from critical to reliable areas. A conditioned least squares formulation of the phase unwrapping problem is the core of the proposed procedure: this allows the solution to be tied to ldquo;some rdquo; known boundary phase values, thus guaranteeing the correct joining of the reconstructed phase in between the different regions and preventing them from being independently unwrapped. The application of the finite element method allows a straightforward implementation of the algorithm in the discrete domain case. Experimental results, carried out on simulated and real interferometric SAR data, show the effectiveness of the proposed algorithm and the improved performances with respect to existing unwrapping procedures},
    Journal = {IEEE Transactions on Geoscience and Remote Sensing},
    Keywords = {2-D phase unwrapping algorithm;boundary phase values;discrete domain case;finite element method;interferometric SAR processing;reconstructed phase;two-dimensional region growing least squares phase unwrapping algorithm;wrapped phase image;geophysical signal processing;least squares approximations;radar imaging;radiowave interferometry;remote sensing by radar;synthetic aperture radar} 
    }
    


  6. Ramon F. Hanssen, Tammy M. Weckwerth, Howard A. Zebker, and Roland Klees. High-Resolution Water Vapor Mapping from Interferometric Radar Measurements. Science, 283(5406):1297-1299, 1999. Keyword(s): Troposphere, Water Vapor, InSAR.
    Abstract: Spaceborne radar interferometric delay measurements were used to infer high-resolution maps of integrated atmospheric water vapor, which can be readily related to meteorological phenomena. Maps of the water vapor distribution associated with a precipitating cloud, a partly precipitating cold front, and horizontal convective rolls reveal quantitative measures that are not observed with conventional methods, and suggest that such radar observations can be used for forecasting and to study atmospheric dynamics.

    @Article{hanssenWeckwerthZebkerKleesSCIENCE1999,
    author = {Hanssen, Ramon F. and Weckwerth, Tammy M. and Zebker, Howard A. and Klees, Roland},
    title = {High-Resolution Water Vapor Mapping from Interferometric Radar Measurements},
    journal = {Science},
    year = {1999},
    volume = {283},
    number = {5406},
    pages = {1297--1299},
    issn = {0036-8075},
    abstract = {Spaceborne radar interferometric delay measurements were used to infer high-resolution maps of integrated atmospheric water vapor, which can be readily related to meteorological phenomena. Maps of the water vapor distribution associated with a precipitating cloud, a partly precipitating cold front, and horizontal convective rolls reveal quantitative measures that are not observed with conventional methods, and suggest that such radar observations can be used for forecasting and to study atmospheric dynamics.},
    doi = {10.1126/science.283.5406.1297},
    eprint = {https://science.sciencemag.org/content/283/5406/1297.full.pdf},
    file = {:hanssenWeckwerthZebkerKleesSCIENCE1999.pdf:PDF},
    keywords = {Troposphere, Water Vapor, InSAR},
    owner = {ofrey},
    publisher = {American Association for the Advancement of Science},
    url = {https://science.sciencemag.org/content/283/5406/1297},
    
    }
    


  7. Xiaotao Huang and Diannong Liang. Gradual RELAX Algorithm for RFI Suppression in UWB-SAR. Electronics Letters, 35(22):1916-1917, October 1999. Keyword(s): SAR Processing, RFI Suppression, Ultra-Wideband SAR, Gradual RELAX Algorithm.
    Abstract: Parametric methods of radio frequency interference (RFI) suppression in ultra-wideband synthetic aperture radar (UWB-SAR) often outperform their non-parametric counterparts at the expense of computational complexity. The authors present a parametric algorithm that gradually applies the RELAX algorithm and results in greatly improved computational efficiency and stability

    @Article{HuangLiang99:RFI,
    Title = {{Gradual RELAX Algorithm for RFI Suppression in UWB-SAR}},
    Author = {Xiaotao Huang and Diannong Liang},
    Month = Oct,
    Number = {22},
    Pages = {1916-1917},
    Url = {http://ieeexplore.ieee.org/iel5/2220/17603/00811049.pdf},
    Volume = {35},
    Year = {1999},
    Abstract = {Parametric methods of radio frequency interference (RFI) suppression in ultra-wideband synthetic aperture radar (UWB-SAR) often outperform their non-parametric counterparts at the expense of computational complexity. The authors present a parametric algorithm that gradually applies the RELAX algorithm and results in greatly improved computational efficiency and stability},
    Journal = {Electronics Letters},
    Keywords = {SAR Processing, RFI Suppression, Ultra-Wideband SAR, Gradual RELAX Algorithm},
    Pdf = {../../../docs/HuangLiang99.pdf} 
    }
    


  8. Guy Indebetouw and Prapong Klysubun. Space-time digital holography: A three-dimensional microscopic imaging scheme with an arbitrary degree of spatial coherence. Applied Physics Letters, 75(14):2017-2019, October 1999. Keyword(s): Fresnel diffraction, holographic interferometry, image reconstruction, light coherence, optical correlation, optical images, optical microscopy;.
    Abstract: An on-line, spatiotemporal, digital holographic method is described and demonstrated experimentally. Using interferometric imaging, each scatterer of a three-dimensional object is encoded as a temporally modulated Fresnel pattern, and recorded on a charge-coupled device. Temporal heterodyning of the signal from each pixel results in a single-sideband, on-line holographic record in digital form. Reconstruction of an image focused on a chosen transverse plane in the object is done by digital correlation with a reconstruction function matched to that plane. The method circumvents most of the drawbacks of both coherent and incoherent holography, and may find applications in three-dimensional imaging and microscopy. #xa9; 1999 American Institute of Physics.

    @Article{4901834,
    author = {Indebetouw, Guy and Klysubun, Prapong},
    journal = {Applied Physics Letters},
    title = {Space-time digital holography: A three-dimensional microscopic imaging scheme with an arbitrary degree of spatial coherence},
    year = {1999},
    issn = {0003-6951},
    month = {oct},
    number = {14},
    pages = {2017-2019},
    volume = {75},
    abstract = {An on-line, spatiotemporal, digital holographic method is described and demonstrated experimentally. Using interferometric imaging, each scatterer of a three-dimensional object is encoded as a temporally modulated Fresnel pattern, and recorded on a charge-coupled device. Temporal heterodyning of the signal from each pixel results in a single-sideband, on-line holographic record in digital form. Reconstruction of an image focused on a chosen transverse plane in the object is done by digital correlation with a reconstruction function matched to that plane. The method circumvents most of the drawbacks of both coherent and incoherent holography, and may find applications in three-dimensional imaging and microscopy. #xa9; 1999 American Institute of Physics.},
    doi = {10.1063/1.124901},
    keywords = {Fresnel diffraction;holographic interferometry;image reconstruction;light coherence;optical correlation;optical images;optical microscopy;},
    
    }
    


  9. Jong-Sen Lee, M.R. Grunes, T.L. Ainsworth, Li-Jen Du, D.L. Schuler, and Shane R. Cloude. Unsupervised classification using polarimetric decomposition and the complex Wishart classifier. IEEE Transactions on Geoscience and Remote Sensing, 37(5):2249-2258, September 1999. Keyword(s): geophysical signal processing, geophysical techniques, image classification, radar imaging, radar polarimetry, remote sensing by radar, synthetic aperture radar, terrain mappingSAR, complex Wishart classifier, complex Wishart distribution, covariance matrix, entropy-alpha plane, geophysical measurement technique, image classification, initial classification map, iteration, land surface, man-made object, maximum likelihood classifier, polarimetric decomposition, polarimetric target decomposition, polarization, radar imaging, radar polarimetry, radar remote sensing, synthetic aperture radar, terrain mapping, terrain type, training, unsupervised classification.
    Abstract: The authors propose a new method for unsupervised classification of terrain types and man-made objects using polarimetric synthetic aperture radar (SAR) data. This technique is a combination of the unsupervised classification based on polarimetric target decomposition, S.R. Cloude et al. (1997), and the maximum likelihood classifier based on the complex Wishart distribution for the polarimetric covariance matrix, J.S. Lee et al. (1994). The authors use Cloude and Pottier's method to initially classify the polarimetric SAR image. The initial classification map defines training sets for classification based on the Wishart distribution. The classified results are then used to define training sets for the next iteration. Significant improvement has been observed in iteration. The iteration ends when the number of pixels switching classes becomes smaller than a predetermined number or when other criteria are met. The authors observed that the class centers in the entropy-alpha plane are shifted by each iteration. The final class centers in the entropy-alpha plane are useful for class identification by the scattering mechanism associated with each zone. The advantages of this method are the automated classification, and the interpretation of each class based on scattering mechanism. The effectiveness of this algorithm is demonstrated using a JPL/AIRSAR polarimetric SAR image

    @Article{leeGrunesAinsworthDuSchulerCloude1999:PolSARDecompForClassification,
    Title = {Unsupervised classification using polarimetric decomposition and the complex Wishart classifier},
    Author = {Jong-Sen Lee and Grunes, M.R. and Ainsworth, T.L. and Li-Jen Du and Schuler, D.L. and Cloude, Shane R.},
    Doi = {10.1109/36.789621},
    ISSN = {0196-2892},
    Month = sep,
    Number = {5},
    Pages = {2249-2258},
    Url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=789621&isnumber=17110},
    Volume = {37},
    Year = {1999},
    Abstract = {The authors propose a new method for unsupervised classification of terrain types and man-made objects using polarimetric synthetic aperture radar (SAR) data. This technique is a combination of the unsupervised classification based on polarimetric target decomposition, S.R. Cloude et al. (1997), and the maximum likelihood classifier based on the complex Wishart distribution for the polarimetric covariance matrix, J.S. Lee et al. (1994). The authors use Cloude and Pottier's method to initially classify the polarimetric SAR image. The initial classification map defines training sets for classification based on the Wishart distribution. The classified results are then used to define training sets for the next iteration. Significant improvement has been observed in iteration. The iteration ends when the number of pixels switching classes becomes smaller than a predetermined number or when other criteria are met. The authors observed that the class centers in the entropy-alpha plane are shifted by each iteration. The final class centers in the entropy-alpha plane are useful for class identification by the scattering mechanism associated with each zone. The advantages of this method are the automated classification, and the interpretation of each class based on scattering mechanism. The effectiveness of this algorithm is demonstrated using a JPL/AIRSAR polarimetric SAR image},
    Journal = {IEEE Transactions on Geoscience and Remote Sensing},
    Keywords = {geophysical signal processing, geophysical techniques, image classification, radar imaging, radar polarimetry, remote sensing by radar, synthetic aperture radar, terrain mappingSAR, complex Wishart classifier, complex Wishart distribution, covariance matrix, entropy-alpha plane, geophysical measurement technique, image classification, initial classification map, iteration, land surface, man-made object, maximum likelihood classifier, polarimetric decomposition, polarimetric target decomposition, polarization, radar imaging, radar polarimetry, radar remote sensing, synthetic aperture radar, terrain mapping, terrain type, training, unsupervised classification},
    Owner = {ofrey},
    Pdf = {../../../docs/leeGrunesAinsworthDuSchulerCloude1999.pdf} 
    }
    


  10. J. Li, Z. Bi, and Z.-S. Liu. Autofocus and feature extraction in curvilinear SAR via a relaxation-based algorithm. Radar, Sonar and Navigation, IEE Proceedings -, 146(4):201-207, 1999. Keyword(s): SAR Processing, Non-Linear Flight Path, SAR Tomography, Curvilinear SAR, error analysis, feature extraction, focusing, radar imaging, synthetic aperture radar, 3D target features, AUTORELAX, CLSAR, SAR imaging, aperture errors compensation, curvilinear SAR, curvilinear synthetic aperture radar, data model, estimation accuracy, experimental results, feature extraction, relaxation-based algorithm, relaxation-based autofocus algorithm, simulation results, target parameters.
    Abstract: The paper presents a relaxation-based autofocus (AUTORELAX) algorithm that can be used to compensate for the aperture errors in curvilinear synthetic aperture radar (CLSAR) and to extract three-dimensional target features. A self-contained detailed derivation of the data model for the autofocus problem in CLSAR is presented. Experimental and simulation results show that AUTORELAX can be used to significantly improve the estimation accuracy of the target parameters.

    @Article{liBiLiu1999:NonLinearSARTomo,
    Title = {{Autofocus and feature extraction in curvilinear SAR via a relaxation-based algorithm}},
    Author = {Li, J. and Bi, Z. and Liu, Z.-S.},
    ISSN = {1350-2395},
    Number = {4},
    Pages = {201--207},
    Url = {http://ieeexplore.ieee.org/iel5/2198/17363/00799030.pdf},
    Volume = {146},
    Year = {1999},
    Abstract = {The paper presents a relaxation-based autofocus (AUTORELAX) algorithm that can be used to compensate for the aperture errors in curvilinear synthetic aperture radar (CLSAR) and to extract three-dimensional target features. A self-contained detailed derivation of the data model for the autofocus problem in CLSAR is presented. Experimental and simulation results show that AUTORELAX can be used to significantly improve the estimation accuracy of the target parameters.},
    Booktitle = {Radar, Sonar and Navigation, IEE Proceedings -},
    Journal = {Radar, Sonar and Navigation, IEE Proceedings -},
    Keywords = {SAR Processing, Non-Linear Flight Path, SAR Tomography, Curvilinear SAR, error analysis, feature extraction, focusing, radar imaging, synthetic aperture radar, 3D target features, AUTORELAX, CLSAR, SAR imaging, aperture errors compensation, curvilinear SAR, curvilinear synthetic aperture radar, data model, estimation accuracy, experimental results, feature extraction, relaxation-based algorithm, relaxation-based autofocus algorithm, simulation results, target parameters},
    Owner = {ofrey},
    Pdf = {../../../docs/liBiLiu1999.pdf} 
    }
    


  11. Richard T. Lord and Michael R. Inggs. Efficient RFI suppression in SAR using LMS adaptive filter integrated with range/Doppler algorithm. Electronics Letters, 35(8):629-630, 1999. Keyword(s): SAR Processing, Doppler radar, adaptive filters, interference suppression, least mean squares methods, radar imaging, radar interference, synthetic aperture radar, Doppler algorithm, LMS adaptive filter, RFI Suppression, SAR image processing, radiofrequency interference, range compression.
    Abstract: Radio frequency interference (RFI) suppression in SAR images often requires a great amount of computation. The authors describe how significant computational savings can be achieved by integrating the RFI suppression stage, implemented with a least-mean-squared (LMS) adaptive filter, with the range compression stage of the range/Doppler SAR processing algorithm

    @Article{lordInggsElLetters99:RFI,
    Title = {Efficient RFI suppression in SAR using LMS adaptive filter integrated with range/Doppler algorithm},
    Author = {Lord, Richard T. and Inggs, Michael R.},
    Number = {8},
    Pages = {629--630},
    Url = {http://ieeexplore.ieee.org/iel5/2220/16707/00770996.pdf},
    Volume = {35},
    Year = {1999},
    Abstract = {Radio frequency interference (RFI) suppression in SAR images often requires a great amount of computation. The authors describe how significant computational savings can be achieved by integrating the RFI suppression stage, implemented with a least-mean-squared (LMS) adaptive filter, with the range compression stage of the range/Doppler SAR processing algorithm},
    Journal = {Electronics Letters},
    Keywords = {SAR Processing, Doppler radar, adaptive filters, interference suppression, least mean squares methods, radar imaging, radar interference, synthetic aperture radar, Doppler algorithm, LMS adaptive filter, RFI Suppression, SAR image processing, radiofrequency interference, range compression},
    Owner = {ofrey},
    Pdf = {../../../docs/lordInggsElLetters99.pdf} 
    }
    


  12. Christian Matzler and Andreas Wiesmann. Extension of the Microwave Emission Model of Layered Snowpacks to Coarse-Grained Snow. Remote Sensing of Environment, 70(3):317-325, December 1999. Keyword(s): MEMLS, Snow, Microwave, Microwave emission model of lalayer snowpacks, Dielectric Properties of Dry Snow, relative permittivity, snow density.
    Abstract: The microwave emission model of layered snowpacks (MEMLS) is a multilayer and multiple-scattering radiative transfer model developed for dry winter snow using an empirical parametrization of the scattering coefficient (se the copanion article). A limitation is in the applicable range of frequencies and correlation lengths. In order to extend the model, a physical determination of the volume-scattering coefficients, describing the coupling between the six fluxes, is developed here, based on the improved Born approximation. An exponential spatial autocorrelation function was selected. With this addition, MEMLS obtains a complete physical basis. The extended model is void of free parameters. The validation was done with two types of experiments made at the alpine test site, Weissfluhjoch: 1) radiometry at 11 GHz, 21 GHz, 35 GHz, 48 GHz, and 94 GHz of winter snow samples on a blackbody and on a metal plate, respectively, and 2) radiometric monitoring at 4.9 GHz, 10.4 GHz, 21 GHz, 35 GHz, and 94 GHz of coarse-grained crusts growing and decaying during melt-and-refreeze cycles. Digitized snow sections were used to measure snow structure in both experiments. The coarsest grains were found in the refrozen crusts with a correlation length up to 0.71 mm; the winter snow samples had smaller values, from 0.035 mm for new snow to about 0.33 mm for depth hoar. Good results have been obtained in all cases studied so far.

    @Article{matzlerWiesmannRSE1999MEMLSRef2ExtensionForCoarseGrainSnow,
    author = {Christian Matzler and Andreas Wiesmann},
    title = {Extension of the Microwave Emission Model of Layered Snowpacks to Coarse-Grained Snow},
    journal = {Remote Sensing of Environment},
    year = {1999},
    volume = {70},
    number = {3},
    pages = {317--325},
    month = {dec},
    abstract = {The microwave emission model of layered snowpacks (MEMLS) is a multilayer and multiple-scattering radiative transfer model developed for dry winter snow using an empirical parametrization of the scattering coefficient (se the copanion article). A limitation is in the applicable range of frequencies and correlation lengths. In order to extend the model, a physical determination of the volume-scattering coefficients, describing the coupling between the six fluxes, is developed here, based on the improved Born approximation. An exponential spatial autocorrelation function was selected. With this addition, MEMLS obtains a complete physical basis. The extended model is void of free parameters. The validation was done with two types of experiments made at the alpine test site, Weissfluhjoch: 1) radiometry at 11 GHz, 21 GHz, 35 GHz, 48 GHz, and 94 GHz of winter snow samples on a blackbody and on a metal plate, respectively, and 2) radiometric monitoring at 4.9 GHz, 10.4 GHz, 21 GHz, 35 GHz, and 94 GHz of coarse-grained crusts growing and decaying during melt-and-refreeze cycles. Digitized snow sections were used to measure snow structure in both experiments. The coarsest grains were found in the refrozen crusts with a correlation length up to 0.71 mm; the winter snow samples had smaller values, from 0.035 mm for new snow to about 0.33 mm for depth hoar. Good results have been obtained in all cases studied so far.},
    doi = {10.1016/s0034-4257(99)00047-4},
    file = {:matzlerWiesmannRSE1999MEMLSRef2ExtensionForCoarseGrainSnow.pdf:PDF},
    keywords = {MEMLS, Snow, Microwave, Microwave emission model of lalayer snowpacks,Dielectric Properties of Dry Snow,relative permittivity, snow density},
    owner = {ofrey},
    pdf = {../../../docs/matzlerWiesmannRSE1999MEMLSRef2ExtensionForCoarseGrainSnow.pdf},
    publisher = {Elsevier {BV}},
    
    }
    


  13. Josef Mittermayer, Alberto Moreira, and Otmar Loffeld. Spotlight SAR data processing using the frequency scaling algorithm. IEEE Trans. Geosci. Remote Sens., 37(5):2198-2214, September 1999. Keyword(s): SAR Processing, Spotlight SAR, dechirp, dechirp-on-receive, Doppler radar, geophysical signal processing, radar imaging, remote sensing by radar, spectral analysis, synthetic aperture radarazimuth processing, azimuth scaling, chirp convolution, frequency scaling algorithm, Chirp Scaling Algorithm, nonchirped SAR signals, nonchirped raw data, range Doppler domain, range cell migration correction, residual video phase, RVP, spectral analysis approach, spotlight SAR data processing, stripmap raw data, subaperture approach.
    Abstract: This paper presents a new processing algorithm for spotlight SAR data processing. The algorithm performs the range cell migration correction for non-chirped raw data without interpolation by using a novel frequency scaling operation. The azimuth processing is based on a spectral analysis approach which is made highly accurate by azimuth scaling. In almost all processing stages, a subaperture approach is introduced for efficient azimuth processing. In this paper, the complete derivation of the algorithm is presented. A very useful formulation for non-chirped SAR signals in the range Doppler domain is also proposed where the residual video phase is expressed by a chirp convolution. The algorithm performance is shown by several simulations. A spotlight image, which has been extracted from stripmap raw data of the experimental SAR system of DLR, shows the validity of the frequency scaling algorithm

    @Article{mittermayerMoreiraLoffeld1999:SpotlightCS,
    Title = {Spotlight SAR data processing using the frequency scaling algorithm},
    Author = {Mittermayer, Josef and Moreira, Alberto and Loffeld, Otmar},
    Doi = {10.1109/36.789617},
    ISSN = {0196-2892},
    Month = {Sep},
    Number = {5},
    Pages = {2198-2214},
    Url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=00789617},
    Volume = {37},
    Year = {1999},
    Abstract = {This paper presents a new processing algorithm for spotlight SAR data processing. The algorithm performs the range cell migration correction for non-chirped raw data without interpolation by using a novel frequency scaling operation. The azimuth processing is based on a spectral analysis approach which is made highly accurate by azimuth scaling. In almost all processing stages, a subaperture approach is introduced for efficient azimuth processing. In this paper, the complete derivation of the algorithm is presented. A very useful formulation for non-chirped SAR signals in the range Doppler domain is also proposed where the residual video phase is expressed by a chirp convolution. The algorithm performance is shown by several simulations. A spotlight image, which has been extracted from stripmap raw data of the experimental SAR system of DLR, shows the validity of the frequency scaling algorithm},
    Journal = {IEEE Trans. Geosci. Remote Sens.},
    Keywords = {SAR Processing, Spotlight SAR, dechirp, dechirp-on-receive, Doppler radar, geophysical signal processing, radar imaging, remote sensing by radar, spectral analysis, synthetic aperture radarazimuth processing, azimuth scaling, chirp convolution, frequency scaling algorithm, Chirp Scaling Algorithm, nonchirped SAR signals, nonchirped raw data, range Doppler domain, range cell migration correction, residual video phase, RVP, spectral analysis approach, spotlight SAR data processing, stripmap raw data, subaperture approach},
    Owner = {ofrey},
    Pdf = {../../../docs/mittermayerMoreiraLoffeld1999.pdf} 
    }
    


  14. Andreas Reigber. Range dependent spectral filtering to minimize the baseline decorrelation in airborne SAR interferometry. 3:1721-1723, 1999. Keyword(s): SAR Processing, SAR Interferometry, Interferometry, InSAR, Range Spectral Filter, Spectral Filter, adaptive signal processing, airborne radar, geophysical signal processing, geophysical techniques, radar imaging, radar theory, remote sensing by radar, synthetic aperture radar, terrain mapping, E-SAR, InSAR, L-band, SAR, Airborne SAR interferometry, Airborne SAR, Baseline Decorrelation, fixed bandwidth filtering, geometric resolution, geophysical measurement technique, interferogram coherence, interferometric SAR, land surface, radar imaging, radar remote sensing, range dependent spectral filtering, repeat-pass, spectral misalignment, synthetic aperture radar, terrain mapping.
    Abstract: This paper discusses two methods to solve the problem of a range-dependent baseline decorrelation occurring especially in airborne repeat-pass SAR interferometry. The first approach allows a fixed bandwidth filtering for the whole range avoiding the spectral misalignment of the standard method. The second approach enables a real adaptive filtering of the range-dependent baseline decorrelation and allows one also to obtain the best geometric resolution for each range position without decreasing the interferogram coherence. The efficiency of the two methods is demonstrated by using interferograms obtained from DLR's E-SAR in the L-band repeat-pass-mode

    @Article{reigberIGARSS1999:InSARRangeSpecFilt,
    Title = {Range dependent spectral filtering to minimize the baseline decorrelation in airborne SAR interferometry},
    Author = {Reigber, Andreas},
    Doi = {10.1109/IGARSS.1999.772073},
    Pages = {1721--1723},
    Url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=772073&isnumber=16741},
    Volume = {3},
    Year = {1999},
    Abstract = {This paper discusses two methods to solve the problem of a range-dependent baseline decorrelation occurring especially in airborne repeat-pass SAR interferometry. The first approach allows a fixed bandwidth filtering for the whole range avoiding the spectral misalignment of the standard method. The second approach enables a real adaptive filtering of the range-dependent baseline decorrelation and allows one also to obtain the best geometric resolution for each range position without decreasing the interferogram coherence. The efficiency of the two methods is demonstrated by using interferograms obtained from DLR's E-SAR in the L-band repeat-pass-mode},
    Booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS '99},
    Keywords = {SAR Processing, SAR Interferometry, Interferometry, InSAR, Range Spectral Filter, Spectral Filter, adaptive signal processing, airborne radar, geophysical signal processing, geophysical techniques, radar imaging, radar theory, remote sensing by radar, synthetic aperture radar, terrain mapping, E-SAR, InSAR, L-band, SAR, Airborne SAR interferometry, Airborne SAR, Baseline Decorrelation, fixed bandwidth filtering, geometric resolution, geophysical measurement technique, interferogram coherence, interferometric SAR, land surface, radar imaging, radar remote sensing, range dependent spectral filtering, repeat-pass, spectral misalignment, synthetic aperture radar, terrain mapping},
    Owner = {ofrey},
    Pdf = {../../../docs/reigberIGARSS1999.pdf} 
    }
    


  15. Ridha Touzi, Armand Lopes, Jérôme Bruniquel, and Paris W. Vachon. Coherence estimation for SAR imagery. IEEE Trans. Geosci. Remote Sens., 37(1):135-149, January 1999. Keyword(s): SAR Processing, SAR imagery, coherence, coherence estimation, coherence map resolution, decorrelation, temporal decorrelation, cross-channel correlation, dual channel method, geophysical measurement technique, land surface, multiple-channel, radar imaging, radar remote sensing, synthetic aperture radar, terrain mapping, unbiased coherence estimate, geophysical signal processing, geophysical techniques, radar imaging, remote sensing by radar, synthetic aperture radar, terrain mapping;.
    Abstract: In dual- or multiple-channel synthetic aperture radar (SAR) imaging modes, cross-channel correlation is a potential source of information. The sample coherence magnitude is calculated over a moving window to generate a coherence magnitude map. High-resolution coherence maps may be useful to discriminate fine structures. Coarser resolution is needed for a more accurate estimation of the coherence magnitude. In this study, the accuracy of coherence estimation is investigated as a function of the coherence map resolution. It is shown that the space-averaged coherence magnitude is biased toward higher values. The accuracy of the coherence magnitude estimate obtained is a function of the number of pixels averaged and the number of independent samples per pixel (i.e., the coherence map resolution). A method is proposed to remove the bias from the space-averaged sample coherence magnitude. Coherence magnitude estimation from complex (magnitude and phase) coherence maps is also considered. It is established that the magnitude of the averaged sample coherence estimate is slightly biased for high-resolution coherence maps and that the bias reduces with coarser resolution. Finally, coherence estimation for nonstationary targets is discussed. It is shown that the averaged sample coherence obtained from complex coherence maps or coherence magnitude maps is suitable for estimation of nonstationary coherence. The averaged sample (complex) coherence permits the calculation of an unbiased coherence estimate, provided that the original signals can be assumed to be locally stationary over a sufficiently coarse resolution cell

    @Article{touziLopesBruniquelVachon1999TGRS_Coherence,
    author = {Ridha Touzi and Armand Lopes and J{\'e}r{\^o}me Bruniquel and Paris W. Vachon},
    title = {Coherence estimation for {SAR} imagery},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {1999},
    volume = {37},
    number = {1},
    pages = {135-149},
    month = jan,
    issn = {0196-2892},
    abstract = {In dual- or multiple-channel synthetic aperture radar (SAR) imaging modes, cross-channel correlation is a potential source of information. The sample coherence magnitude is calculated over a moving window to generate a coherence magnitude map. High-resolution coherence maps may be useful to discriminate fine structures. Coarser resolution is needed for a more accurate estimation of the coherence magnitude. In this study, the accuracy of coherence estimation is investigated as a function of the coherence map resolution. It is shown that the space-averaged coherence magnitude is biased toward higher values. The accuracy of the coherence magnitude estimate obtained is a function of the number of pixels averaged and the number of independent samples per pixel (i.e., the coherence map resolution). A method is proposed to remove the bias from the space-averaged sample coherence magnitude. Coherence magnitude estimation from complex (magnitude and phase) coherence maps is also considered. It is established that the magnitude of the averaged sample coherence estimate is slightly biased for high-resolution coherence maps and that the bias reduces with coarser resolution. Finally, coherence estimation for nonstationary targets is discussed. It is shown that the averaged sample coherence obtained from complex coherence maps or coherence magnitude maps is suitable for estimation of nonstationary coherence. The averaged sample (complex) coherence permits the calculation of an unbiased coherence estimate, provided that the original signals can be assumed to be locally stationary over a sufficiently coarse resolution cell},
    doi = {10.1109/36.739146},
    file = {:touziLopesBruniquelVachon1999TGRS_Coherence.pdf:PDF},
    keywords = {SAR Processing, SAR imagery,coherence;coherence estimation;coherence map resolution;decorrelation, temporal decorrelation, cross-channel correlation;dual channel method;geophysical measurement technique;land surface;multiple-channel;radar imaging;radar remote sensing;synthetic aperture radar;terrain mapping;unbiased coherence estimate;geophysical signal processing;geophysical techniques;radar imaging;remote sensing by radar;synthetic aperture radar;terrain mapping;},
    owner = {ofrey},
    pdf = {../../../docs/touziLopesBruniquelVachon1999TGRS_Coherence.pdf},
    
    }
    


  16. R. N. Treuhaft and S. R. Cloude. The structure of oriented vegetation from polarimetric interferometry. IEEE Trans. Geosci. Remote Sens., 37(5):2620-2624, September 1999. Keyword(s): SAR Processing, Forest, Forest parameters, biomass, forest canopy, forestry, geophysical measurement technique, height, oriented object, oriented vegetation, oriented-vegetation volume, polarimetric interferometry, radar polarimetry, radar remote sensing, randomly oriented volume, single-baseline polarimetric interferometry, underlying topography, vegetated land surface, vegetation mapping, geophysical techniques, radar polarimetry, remote sensing by radar, vegetation mapping.
    Abstract: Polarimetric radar interferometry is much more sensitive to the distribution of oriented objects in a vegetated land surface than either polarimetry or interferometry alone. This paper shows that single-baseline polarimetric interferometry can be used to estimate the heights of oriented-vegetation volumes and underlying topography, while at least two baselines are needed for randomly oriented volumes. Single-baseline, calculated vegetation-height accuracies are in the range of 2-8 m for reasonable levels of vegetation orientation in forest canopies

    @Article{treuhaftCloude1999:PolINSAROrientedVegetation,
    Title = {The structure of oriented vegetation from polarimetric interferometry},
    Author = {Treuhaft, R. N. and Cloude, S. R.},
    Doi = {10.1109/36.789657},
    ISSN = {0196-2892},
    Month = sep,
    Number = {5},
    Pages = {2620-2624},
    Volume = {37},
    Year = {1999},
    Abstract = {Polarimetric radar interferometry is much more sensitive to the distribution of oriented objects in a vegetated land surface than either polarimetry or interferometry alone. This paper shows that single-baseline polarimetric interferometry can be used to estimate the heights of oriented-vegetation volumes and underlying topography, while at least two baselines are needed for randomly oriented volumes. Single-baseline, calculated vegetation-height accuracies are in the range of 2-8 m for reasonable levels of vegetation orientation in forest canopies},
    Journal = {IEEE Trans. Geosci. Remote Sens.},
    Keywords = {SAR Processing, Forest, Forest parameters, biomass,forest canopy;forestry;geophysical measurement technique;height;oriented object;oriented vegetation;oriented-vegetation volume;polarimetric interferometry;radar polarimetry;radar remote sensing;randomly oriented volume;single-baseline polarimetric interferometry;underlying topography;vegetated land surface;vegetation mapping;geophysical techniques;radar polarimetry;remote sensing by radar;vegetation mapping} 
    }
    


  17. Andreas Wiesmann and Christian Matzler. Microwave emission model of layered snowpacks. Remote Sensing of Environment, 70(3):307-316, 1999. Keyword(s): MEMLS, Snow, Microwave, Microwave emission model of lalayer snowpacks, Dielectric Properties of Dry Snow, relative permittivity, snow density.
    Abstract: A thermal microwave emission model of layered snowpacks (MEMLS) was developed for the frequency range 5-100 GHz. It is based on radiative transfer, using six-flux theory to describe multiple volume scattering and absorption, including radiation trapping due to total reflection and a combination of coherent and incoherent superpositions of reflections between layer interfaces. The scattering coefficient is determined empirically from measured snow samples, whereas the absorption coefficient, the effective permittivity, refraction, and reflection at layer interfaces are based on physical models and on measured ice dielectric properties. The number of layers is only limited by computer time and memory. A limitation of the empirical fits and thus of MEMLS is in the range of observed frequencies and correlation lengths (a measure of grain size). First model validation for dry winter snow was successful. An extension to larger grains is given in a companion article (Matzler and Wiesmann, 1999). The objective of the present article is to describe and illustrate the model and to pave the way for further improvements. MEMLS has been coded in MATLAB. It forms part of a combined land-surface-atmosphere microwave emission model for radiometry from satellites (Pulliainen et al., 1998).

    @Article{wiesmannMatzlerRSE1999MEMLSReferencePaper,
    author = {Wiesmann, Andreas and Matzler, Christian},
    title = {Microwave emission model of layered snowpacks},
    journal = {Remote Sensing of Environment},
    year = {1999},
    volume = {70},
    number = {3},
    pages = {307--316},
    abstract = {A thermal microwave emission model of layered snowpacks (MEMLS) was developed for the frequency range 5-100 GHz. It is based on radiative transfer, using six-flux theory to describe multiple volume scattering and absorption, including radiation trapping due to total reflection and a combination of coherent and incoherent superpositions of reflections between layer interfaces. The scattering coefficient is determined empirically from measured snow samples, whereas the absorption coefficient, the effective permittivity, refraction, and reflection at layer interfaces are based on physical models and on measured ice dielectric properties. The number of layers is only limited by computer time and memory. A limitation of the empirical fits and thus of MEMLS is in the range of observed frequencies and correlation lengths (a measure of grain size). First model validation for dry winter snow was successful. An extension to larger grains is given in a companion article (Matzler and Wiesmann, 1999). The objective of the present article is to describe and illustrate the model and to pave the way for further improvements. MEMLS has been coded in MATLAB. It forms part of a combined land-surface-atmosphere microwave emission model for radiometry from satellites (Pulliainen et al., 1998).},
    doi = {10.1016/s0034-4257(99)00046-2},
    file = {:wiesmannMatzlerRSE1999MEMLSReferencePaper.pdf:PDF},
    keywords = {MEMLS, Snow, Microwave, Microwave emission model of lalayer snowpacks,Dielectric Properties of Dry Snow,relative permittivity, snow density},
    owner = {ofrey},
    pdf = {../../../docs/wiesmannMatzlerRSE1999MEMLSReferencePaper.pdf},
    publisher = {Elsevier},
    
    }
    


  18. Wei Ye, Tat Soon Yeo, and Zheng Bao. Weighted least-squares estimation of phase errors for SAR/ISAR autofocus. IEEE Transactions on Geoscience and Remote Sensing, 37(5):2487-2494, September 1999. Keyword(s): SAR Processsing, Autofocus, Weighted Least-Squares Estimation, WLS, Residual Motion Errors, geophysical techniques, measurement errors, remote sensing by radar, synthetic aperture radar, terrain mapping, ISAR, SAR, geophysical measurement technique, inverse SAR, land surface, phase error, phase error estimation, phase errors, radar remote sensing, synthetic aperture radar, terrain mapping.
    Abstract: A new method of phase error estimation that utilizes the weighted least-squares (WLS) algorithm is presented for synthetic aperture radar (SAR)/inverse SAR (ISAR) autofocus applications. The method does not require that the signal in each range bin be of a certain distribution model, and thus it is robust for many kinds of scene content. The most attractive attribute of the new method is that it can be used to estimate all kinds of phase errors, no matter whether they are of low order, high order, or random. Compared with other methods, the WLS estimation is optimal in the sense that it has the minimum variance of the estimation error. Excellent results have been obtained in autofocusing and imaging experiments on real SAR and ISAR data

    @Article{yeYeoBao1999:Autofocus,
    Title = {{Weighted least-squares estimation of phase errors for SAR/ISAR autofocus}},
    Author = {Wei Ye and Tat Soon Yeo and Zheng Bao},
    Doi = {10.1109/36.789644},
    Month = {sep},
    Number = {5},
    Pages = {2487--2494},
    Url = {http://ieeexplore.ieee.org/iel5/36/17111/00789644.pdf},
    Volume = {37},
    Year = {1999},
    Abstract = {A new method of phase error estimation that utilizes the weighted least-squares (WLS) algorithm is presented for synthetic aperture radar (SAR)/inverse SAR (ISAR) autofocus applications. The method does not require that the signal in each range bin be of a certain distribution model, and thus it is robust for many kinds of scene content. The most attractive attribute of the new method is that it can be used to estimate all kinds of phase errors, no matter whether they are of low order, high order, or random. Compared with other methods, the WLS estimation is optimal in the sense that it has the minimum variance of the estimation error. Excellent results have been obtained in autofocusing and imaging experiments on real SAR and ISAR data},
    Journal = {IEEE Transactions on Geoscience and Remote Sensing},
    Keywords = {SAR Processsing, Autofocus, Weighted Least-Squares Estimation, WLS, Residual Motion Errors, geophysical techniques, measurement errors, remote sensing by radar, synthetic aperture radar, terrain mapping,ISAR, SAR, geophysical measurement technique, inverse SAR, land surface, phase error, phase error estimation, phase errors, radar remote sensing, synthetic aperture radar, terrain mapping},
    Pdf = {../../../docs/yeYeoBao1999.pdf} 
    }
    


Conference articles

  1. Alain Arnaud. Ship detection by SAR interferometry. In Proc. IEEE Int. Geosci. Remote Sens. Symp., volume 5, pages 2616-2618 vol.5, June 1999. Keyword(s): ships, radar detection, synthetic aperture radar, radar imaging, marine radar, naval radar, marine radar, ship detection, SAR interferometry, InSAR, synthetic aperture radar, radar imaging, small ship, agitated sea surface, low incidence angle, method, coherence, phase, phase coherence, Marine vehicles, Interferometry, Synthetic aperture radar, Satellites, Electromagnetic scattering, Radar detection, Sea surface, Backscatter, Azimuth, Phase detection.
    @InProceedings{arnaudIGARSS1999ShipDetectionBySARInterferometry,
    author = {Alain Arnaud},
    title = {Ship detection by {SAR} interferometry},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {1999},
    volume = {5},
    pages = {2616--2618 vol.5},
    month = jun,
    doi = {10.1109/IGARSS.1999.771594},
    file = {:arnaudIGARSS1999ShipDetectionBySARInterferometry.pdf:PDF},
    keywords = {ships, radar detection, synthetic aperture radar, radar imaging, marine radar, naval radar, marine radar, ship detection, SAR interferometry, InSAR, synthetic aperture radar, radar imaging, small ship, agitated sea surface, low incidence angle, method, coherence, phase, phase coherence, Marine vehicles, Interferometry, Synthetic aperture radar, Satellites, Electromagnetic scattering, Radar detection, Sea surface, Backscatter, Azimuth, Phase detection},
    owner = {ofrey},
    
    }
    


  2. Güner Arslan, Magesh Valliappan, and Brian L. Evans. Quality Assessment of Compression Techniques for Synthetic Aperture Radar Images. In International Conference on Image Processing, ICIP 1999, volume 3, pages 857-861, October 1999. Keyword(s): Data Compression, Quality Assessment, Quality Measures, Edge Correlation Quality Measure.
    Abstract: Synthetic aperture radar (SAR) systems are mounted on airplanes and satellites, which have limited downlink and storage capacity, yet SAR image sequences may be produced at rates of several Gbps. Compression is difficult because SAR images contain significant high-frequency information, such as terrain boundaries and terrain texture. In assessing the quality of compressed images, peak signal-to-noise ratio and men-squared error are inadequate because they assume that distortion is solely due to image-independent additive noise. In this paper, we provide objective measures to assess the visual quality of SAR images compressed by JPEG and SPIHT coders. The human visual system responds differently to linear distortion and noise injection (nonlinear distortion plus additive noise). Our key contributions are that we first decouple and quantify the linear distortion and noise injection in JPEG and SPIHT coders, and second introduce a new edge correlation quality measure which we use to quantify nonlinear distortion

    @InProceedings{ArslVallEvans99:Quali,
    Title = {{Quality Assessment of Compression Techniques for Synthetic Aperture Radar Images}},
    Author = {G{\"u}ner Arslan and Magesh Valliappan and Brian L. Evans},
    Booktitle = {International Conference on Image Processing, ICIP 1999},
    Month = Oct,
    Pages = {857-861},
    Url = {http://ieeexplore.ieee.org/iel5/6632/17691/00817262.pdf},
    Volume = {3},
    Year = {1999},
    Abstract = {Synthetic aperture radar (SAR) systems are mounted on airplanes and satellites, which have limited downlink and storage capacity, yet SAR image sequences may be produced at rates of several Gbps. Compression is difficult because SAR images contain significant high-frequency information, such as terrain boundaries and terrain texture. In assessing the quality of compressed images, peak signal-to-noise ratio and men-squared error are inadequate because they assume that distortion is solely due to image-independent additive noise. In this paper, we provide objective measures to assess the visual quality of SAR images compressed by JPEG and SPIHT coders. The human visual system responds differently to linear distortion and noise injection (nonlinear distortion plus additive noise). Our key contributions are that we first decouple and quantify the linear distortion and noise injection in JPEG and SPIHT coders, and second introduce a new edge correlation quality measure which we use to quantify nonlinear distortion},
    Keywords = {Data Compression, Quality Assessment, Quality Measures, Edge Correlation Quality Measure},
    Pdf = {../../../docs/ArslVallEvans99.pdf} 
    }
    


  3. M. Bara, J. Monne, and A. Broquetas. Navigation systems requirements for airborne interferometric SAR platforms. In Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International, volume 4, pages 2158-2160, July 1999.
    @InProceedings{Bara1999,
    Title = {Navigation systems requirements for airborne interferometric SAR platforms},
    Author = {Bara, M. and Monne, J. and Broquetas, A.},
    Booktitle = {Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International},
    Doi = {10.1109/IGARSS.1999.775062},
    Month = Jul,
    Pages = {2158--2160},
    Volume = {4},
    Year = {1999},
    Owner = {ofrey},
    Timestamp = {2009.03.05} 
    }
    


  4. M. Bara, O. Mora, M. Romero, and A. Broquetas. Generation of precise wide-area geocoded elevation models with ERS SAR data. In Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International, volume 4, pages 1924-1926, July 1999.
    @InProceedings{Bara1999a,
    Title = {Generation of precise wide-area geocoded elevation models with ERS SAR data},
    Author = {Bara, M. and Mora, O. and Romero, M. and Broquetas, A.},
    Booktitle = {Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International},
    Doi = {10.1109/IGARSS.1999.774988},
    Month = Jul,
    Pages = {1924--1926},
    Volume = {4},
    Year = {1999},
    Owner = {ofrey},
    Timestamp = {2009.03.05} 
    }
    


  5. Svante Björklund and David Rejdemyhr. A MATLAB Toolbox for Radar Array Processing. In ISSPA '99, International Symposium on Signal Processing and its Applications, pages 547-550, 1999. Keyword(s): Radar Array Processing, MATLAB Toolbox for Radar Array Processing.
    Abstract: This paper describes the design, implemented possibilities and usage of a MATLAB Toolbox for radar signal processing. The Toolbox is especially suited for processing in the spatial dimension using signals from an antenna array. Both simulated and measured signals can be used. Both conventional processing, e.g. conventional beamforming, and model based processing is possible.

    @InProceedings{Bjorklund:MatlabToolbox,
    Title = {{A MATLAB Toolbox for Radar Array Processing}},
    Author = {Svante Bj{\"o}rklund and David Rejdemyhr},
    Booktitle = {ISSPA '99, International Symposium on Signal Processing and its Applications},
    Pages = {547-550},
    Url = {http://www.control.isy.liu.se/~svabj/dbt/dbtisspa99.pdf},
    Year = {1999},
    Abstract = {This paper describes the design, implemented possibilities and usage of a MATLAB Toolbox for radar signal processing. The Toolbox is especially suited for processing in the spatial dimension using signals from an antenna array. Both simulated and measured signals can be used. Both conventional processing, e.g. conventional beamforming, and model based processing is possible.},
    Keywords = {Radar Array Processing, MATLAB Toolbox for Radar Array Processing},
    Pdf = {../../../docs/dbtisspa99.pdf} 
    }
    


  6. G. Connan, H. D. Griffiths, P. V. Brennan, and R. Garello. W-band radar measurements of laboratory water waves. In OCEANS '99 MTS/IEEE. Riding the Crest into the 21st Century, volume 3, pages 1333-1337 vol.3, 1999. Keyword(s): SAR Processing, W-Band, backscatter, ocean waves, oceanographic techniques, radar cross-sections, remote sensing by radar, synthetic aperture radar, 75 to 110 GHz, 94 GHz, EHF, FMCW radar, SAR, W-band, backscattering, internal wave, measurement technique, millimetre wave radar, ocean wave, radar remote sensing, radar scattering, synthetic aperture radar, wave-tank experiment, Chirp modulation, Frequency modulation, Laboratories, Radar antennas, Radar imaging, Radar measurements, Sea surface, Signal resolution, Surface waves, Synthetic aperture radar.
    Abstract: The paper presents results on millimetre wave radar backscattering from laboratory water waves. Firstly, in a linear wave-tank, the radar has sensed mechanically generated surface waves of varying frequency (1 to 4 Hz) and amplitude (0.5 to 10 cm). Finally, in a 13 m diameter wave-tank, scaled versions of particular internal wave phenomena have been set-up under mechanically generated surface waves, and the resulting wave-field has been sensed by the radar in SAR mode. Both series of experiments have been carried out at the Laboratoire des Ecoulements Geophysiques et Industriels, Grenoble, France, within the EC project Mesoscale Ocean Radar Signature Experiments. First, the role of the radar and its operating mode are briefly presented, and the experiments are described. Then, the paper focuses on the data analysis and draws some conclusions on the backscattering mechanisms

    @INPROCEEDINGS{connanGriffithsBrennanGarelloOCEANS1999FMCWSARWBAND,
    author={G. Connan and H. D. Griffiths and P. V. Brennan and R. Garello},
    booktitle={OCEANS '99 MTS/IEEE. Riding the Crest into the 21st Century},
    title={W-band radar measurements of laboratory water waves},
    year={1999},
    volume={3},
    number={},
    pages={1333-1337 vol.3},
    abstract={The paper presents results on millimetre wave radar backscattering from laboratory water waves. Firstly, in a linear wave-tank, the radar has sensed mechanically generated surface waves of varying frequency (1 to 4 Hz) and amplitude (0.5 to 10 cm). Finally, in a 13 m diameter wave-tank, scaled versions of particular internal wave phenomena have been set-up under mechanically generated surface waves, and the resulting wave-field has been sensed by the radar in SAR mode. Both series of experiments have been carried out at the Laboratoire des Ecoulements Geophysiques et Industriels, Grenoble, France, within the EC project Mesoscale Ocean Radar Signature Experiments. First, the role of the radar and its operating mode are briefly presented, and the experiments are described. Then, the paper focuses on the data analysis and draws some conclusions on the backscattering mechanisms},
    keywords={SAR Processing, W-Band,backscatter;ocean waves;oceanographic techniques;radar cross-sections;remote sensing by radar;synthetic aperture radar;75 to 110 GHz;94 GHz;EHF;FMCW radar;SAR;W-band;backscattering;internal wave;measurement technique;millimetre wave radar;ocean wave;radar remote sensing;radar scattering;synthetic aperture radar;wave-tank experiment;Chirp modulation;Frequency modulation;Laboratories;Radar antennas;Radar imaging;Radar measurements;Sea surface;Signal resolution;Surface waves;Synthetic aperture radar},
    doi={10.1109/OCEANS.1999.800187},
    ISSN={},
    month={},
    owner = {ofrey},
    
    }
    


  7. Ian G. Cumming, Frank Wong, and Bob Hawkins. RADARSAT-1 Doppler Centroid Estimation Using Phase-Based Estimators. In CEOS SAR Workshop 1999, 1999. Keyword(s): SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Multilook Cross Correlation, MLCC, Multilook Beat Frequency, MLBF, Clutterlock, Doppler Ambiguity Resolver, DAR, Satellite SAR.
    Abstract: Doppler Centroid (DOPCEN) estimation continues to be an important and sometimes overlooked component of SAR processing. This is especially true in the case of ScanSAR, where the estimate must be accurate to approximately 5 Hz in order to avoid radiometric artifacts in the processed images. In the last 10 years, a new class of estimator has been developed based on the phase of the received signal, rather than on the spectral amplitude. The concepts were developed by Madsen, Bamler and Runge, and more recently by Wong and Cumming. It is generally acknowledged that the phase-based estimators can be more accurate than the amplitude-based estimators, provided their limitations are understood, and they are applied properly. We consider the DLR (Bamler & Runge), the MLCC and the MLBF (the latter two both Wong & Cumming). We show how their performance differs as a function of radiometric discontinuities, partially-exposed targets, noise levels, scene contrast and radar squint angle. The 3 algorithms provide different estimation accuracies with respect to each of these data attributes. RADARSAT data has tighter DOPCEN estimation requirements, because of ScanSAR operation, and because of its higher noise equivalent sigma naught. We have made improvements to the existing phase-based estimators and tested their performance on RADARSAT data. In the paper, we will review the operation of the DOPCEN algorithms, compare their performance, and explain why it is advantageous to use an algorithm which combines features of more than one of the 3 algorithms. Finally, we describe our recommendations for a reliable, combined algorithm.

    @InProceedings{cum:DopCentrEst,
    Title = {{RADARSAT-1 Doppler Centroid Estimation Using Phase-Based Estimators}},
    Author = {Ian G. Cumming and Frank Wong and Bob Hawkins},
    Booktitle = {CEOS SAR Workshop 1999},
    Url = {http://www.estec.esa.nl/ceos99/papers/p168.pdf},
    Year = {1999},
    Abstract = {Doppler Centroid (DOPCEN) estimation continues to be an important and sometimes overlooked component of SAR processing. This is especially true in the case of ScanSAR, where the estimate must be accurate to approximately 5 Hz in order to avoid radiometric artifacts in the processed images. In the last 10 years, a new class of estimator has been developed based on the phase of the received signal, rather than on the spectral amplitude. The concepts were developed by Madsen, Bamler and Runge, and more recently by Wong and Cumming. It is generally acknowledged that the phase-based estimators can be more accurate than the amplitude-based estimators, provided their limitations are understood, and they are applied properly. We consider the DLR (Bamler & Runge), the MLCC and the MLBF (the latter two both Wong & Cumming). We show how their performance differs as a function of radiometric discontinuities, partially-exposed targets, noise levels, scene contrast and radar squint angle. The 3 algorithms provide different estimation accuracies with respect to each of these data attributes. RADARSAT data has tighter DOPCEN estimation requirements, because of ScanSAR operation, and because of its higher noise equivalent sigma naught. We have made improvements to the existing phase-based estimators and tested their performance on RADARSAT data. In the paper, we will review the operation of the DOPCEN algorithms, compare their performance, and explain why it is advantageous to use an algorithm which combines features of more than one of the 3 algorithms. Finally, we describe our recommendations for a reliable, combined algorithm.},
    Keywords = {SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Multilook Cross Correlation, MLCC, Multilook Beat Frequency, MLBF, Clutterlock, Doppler Ambiguity Resolver, DAR, Satellite SAR},
    Pdf = {../../../docs/CummWongHawk99.pdf} 
    }
    


  8. Marina Dragosevic. On Accuracy of Attitude Estimation and Doppler Tracking. In CEOS SAR Workshop 1999, 1999. Keyword(s): SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Doppler Tracker, Attitude Angles, Doppler Ambiguity Resolver, DAR, Satellite SAR.
    Abstract: A precise physical model of the Doppler effects is based on the spacecraft state vectors, earth model and spacecraft attitude. Thus, the problem of Doppler tracking can be posed as the problem of adaptive estimation of the satellite attitude. The same physical model and general approach to Doppler/attitude tracking can be applied to ERS and RADARSAT. However, in the case of RADARSAT there are two additional problems: 1) Since RADARSAT is not zero-Doppler steered, attitude estimation must be combined with PRF (pulse repetition frequency) ambiguity resolution. An efficient and reliable method that achieves this will be presented and discussed. 2) For RADARSAT there is a beam peak dislocation in the azimuth direction and the amount of this dislocation depends on the elevation angle. This is especially significant for the wide beams and for ScanSAR due to the large elevation aperture of the combined beams. It is shown how this effect can be modeled as equivalent elevation-dependent yaw and pitch in addition to the ordinary (very small) RADARSAT attitude angles. It is also shown how these equivalent yaw and pitch values can be incorporated in the generic Doppler centroid model. This representation of the beam peak dislocation feature is very useful because it facilitates the verification of the existing (or new) characterizations of the RADARSAT beam peak dislocation. Ideally, when the elevation-dependent yaw and pitch is taken into account, all beams should provide the same value for the true attitude (via independent Doppler centroid measurements). Thus, a mismatch can be used to correct the dislocation model. Based on these geometric/kinematic models, a complete procedure for very accurate Doppler and attitude tracking for ERS, RADARSAT single beam and RADARSAT ScanSAR modes will be outlined. Results regarding theoretical estimation accuracy and observed variability will be compared. The paper will include comparison with other similar published methods and results. For ScanSAR, all beams are used simultaneously and the sensitivity of the attitude estimates to the proper beam dislocation modeling will be considered.

    @InProceedings{dragosevic99:DopCentrEst,
    Title = {{On Accuracy of Attitude Estimation and Doppler Tracking}},
    Author = {Marina Dragosevic},
    Booktitle = {CEOS SAR Workshop 1999},
    Url = {http://www.estec.esa.nl/ceos99/papers/p164.pdf},
    Year = {1999},
    Abstract = {A precise physical model of the Doppler effects is based on the spacecraft state vectors, earth model and spacecraft attitude. Thus, the problem of Doppler tracking can be posed as the problem of adaptive estimation of the satellite attitude. The same physical model and general approach to Doppler/attitude tracking can be applied to ERS and RADARSAT. However, in the case of RADARSAT there are two additional problems: 1) Since RADARSAT is not zero-Doppler steered, attitude estimation must be combined with PRF (pulse repetition frequency) ambiguity resolution. An efficient and reliable method that achieves this will be presented and discussed. 2) For RADARSAT there is a beam peak dislocation in the azimuth direction and the amount of this dislocation depends on the elevation angle. This is especially significant for the wide beams and for ScanSAR due to the large elevation aperture of the combined beams. It is shown how this effect can be modeled as equivalent elevation-dependent yaw and pitch in addition to the ordinary (very small) RADARSAT attitude angles. It is also shown how these equivalent yaw and pitch values can be incorporated in the generic Doppler centroid model. This representation of the beam peak dislocation feature is very useful because it facilitates the verification of the existing (or new) characterizations of the RADARSAT beam peak dislocation. Ideally, when the elevation-dependent yaw and pitch is taken into account, all beams should provide the same value for the true attitude (via independent Doppler centroid measurements). Thus, a mismatch can be used to correct the dislocation model. Based on these geometric/kinematic models, a complete procedure for very accurate Doppler and attitude tracking for ERS, RADARSAT single beam and RADARSAT ScanSAR modes will be outlined. Results regarding theoretical estimation accuracy and observed variability will be compared. The paper will include comparison with other similar published methods and results. For ScanSAR, all beams are used simultaneously and the sensitivity of the attitude estimates to the proper beam dislocation modeling will be considered.},
    Keywords = {SAR Processing, Doppler Centroid, Doppler Centroid Estimation, Clutterlock, Doppler Tracker, Attitude Angles, Doppler Ambiguity Resolver, DAR, Satellite SAR},
    Pdf = {../../../docs/dragosevic99.pdf} 
    }
    


  9. Gerard J. Genello(Jr.), Michael C. Wicks, and Mehrdad Soumekh. Alias-free Processing of P-3 Data. In Edmund G. Zelnio, editor, Algorithms for Synthetic Aperture Radar Imagery VI, volume SPIE 3721, pages 189-200, 1999. Keyword(s): SAR Processing, Back-Projection, Wavefront Reconstruction, Wavenumber Domain Algorithm, omega-k, RFI Suppression, Digital Spotlighting, Slow-Time Upsampling, Alias-free Processing, P-Band, Ultra-Wideband SAR, FOPEN, Airborne SAR.
    Abstract: This paper is concerned with multidimensional signal processing and image formation with FOliage PENetrating (FOPEN) airborne radar data which were collected by a Navy P-3 ultra wideband (UWB) radar in 1995 [Raw]. A commonly-used assumption for the processing of the P-3 data is that the beamwidth angle of the radar is limited to 35 degrees [Bes],[Goo]; provided that this assumption is valid, the PRF of the P-3 SAR system yields alias-free data in the slow-time Doppler domain. However, controlled measurements with the P-3 radar have indicated a beamwidth which exceeds 35 degrees [Raw]. In this paper, we examine a method for processing of the P-3 data in which the incorrect assumption that its radar beamwidth angle is limited to 35 degrees is not imposed. In this approach, a SAR processing scheme which enables the user to extract the SAR signature of a specific target area (digital spotlighting) is used to ensure that the resultant reconstructed SAR image is not aliased [S94], [S95], [S99]. The images which are formed via this method with 8192 pulses are shown to be superior in quality to the images which are formed via the conventional P-3 processor with 16386 pulses which was developed at the MIT Lincoln Laboratory [Bes]. In the presentation, we also introduce a method for converting the P-3 deramped data into its alias-free baseband echoed data; the signature of the Radio Frequency Interference (RFI) signals in the two-dimensional spectral domain of the resultant data is examined.

    @InProceedings{GenelloWicksSoumekh99:Aliasfree,
    Title = {{Alias-free Processing of P-3 Data}},
    Author = {Gerard J. Genello(Jr.) and Michael C. Wicks and Mehrdad Soumekh},
    Booktitle = {Algorithms for Synthetic Aperture Radar Imagery VI},
    Editor = {Edmund G. Zelnio},
    Pages = {189-200},
    Url = {http://www.spie.org/scripts/abstract.pl?bibcode=1999SPIE.3721..189G},
    Volume = {SPIE 3721},
    Year = {1999},
    Abstract = {This paper is concerned with multidimensional signal processing and image formation with FOliage PENetrating (FOPEN) airborne radar data which were collected by a Navy P-3 ultra wideband (UWB) radar in 1995 [Raw]. A commonly-used assumption for the processing of the P-3 data is that the beamwidth angle of the radar is limited to 35 degrees [Bes],[Goo]; provided that this assumption is valid, the PRF of the P-3 SAR system yields alias-free data in the slow-time Doppler domain. However, controlled measurements with the P-3 radar have indicated a beamwidth which exceeds 35 degrees [Raw]. In this paper, we examine a method for processing of the P-3 data in which the incorrect assumption that its radar beamwidth angle is limited to 35 degrees is not imposed. In this approach, a SAR processing scheme which enables the user to extract the SAR signature of a specific target area (digital spotlighting) is used to ensure that the resultant reconstructed SAR image is not aliased [S94], [S95], [S99]. The images which are formed via this method with 8192 pulses are shown to be superior in quality to the images which are formed via the conventional P-3 processor with 16386 pulses which was developed at the MIT Lincoln Laboratory [Bes]. In the presentation, we also introduce a method for converting the P-3 deramped data into its alias-free baseband echoed data; the signature of the Radio Frequency Interference (RFI) signals in the two-dimensional spectral domain of the resultant data is examined.},
    Keywords = {SAR Processing, Back-Projection, Wavefront Reconstruction, Wavenumber Domain Algorithm, omega-k, RFI Suppression, Digital Spotlighting, Slow-Time Upsampling, Alias-free Processing, P-Band, Ultra-Wideband SAR, FOPEN, Airborne SAR},
    Pdf = {../../../docs/GenelloWicksSoumekh99.pdf} 
    }
    


  10. Rüdiger Gens. On Phase Unwrapping Based on Minimum Cost Flow Networks. In FRINGE '99, Advancing ERS SAR Interferometry from Applications towards Operations, 1999. Keyword(s): SAR Processing, Interferometry, Phase Unwrapping, Minimum Cost Flow.
    Abstract: Phase unwrapping is a key step in the SAR interferometric processing chain as it converts the phase information derived from an interferometric image pair into valuable height information. Many algorithms have been developed to solve the phase unwrapping problem. None of the algorithms implemented so far has met with all the requirements for an optimal solution. Recently, a very promising approach has been introduced by Costantini (1998). The new method formulates the phase unwrapping problem as a global minimisation problem which can be solved by using minimum cost flow (MCF) networks. These MCF networks in general have been well studied and efficient algorithms exist. However, application of the MCF for phase unwrapping is a new approach and requires further research. This paper deals with the investigation of this particular algorithm and focuses on the optimisation of the cost function used to define the MCF network.

    @InProceedings{gens99:phaseUnWrap,
    Title = {{On Phase Unwrapping Based on Minimum Cost Flow Networks}},
    Author = {R{\"u}diger Gens},
    Booktitle = {FRINGE '99, Advancing ERS SAR Interferometry from Applications towards Operations},
    Url = {http://earth.esa.int/pub/ESA_DOC/fringe1999/Papers/gens.pdf},
    Year = {1999},
    Abstract = {Phase unwrapping is a key step in the SAR interferometric processing chain as it converts the phase information derived from an interferometric image pair into valuable height information. Many algorithms have been developed to solve the phase unwrapping problem. None of the algorithms implemented so far has met with all the requirements for an optimal solution. Recently, a very promising approach has been introduced by Costantini (1998). The new method formulates the phase unwrapping problem as a global minimisation problem which can be solved by using minimum cost flow (MCF) networks. These MCF networks in general have been well studied and efficient algorithms exist. However, application of the MCF for phase unwrapping is a new approach and requires further research. This paper deals with the investigation of this particular algorithm and focuses on the optimisation of the cost function used to define the MCF network.},
    Keywords = {SAR Processing, Interferometry, Phase Unwrapping, Minimum Cost Flow},
    Pdf = {../../../docs/gens99.pdf} 
    }
    


  11. Harry Jackson, Ian Sinclair, and Sebastian Tam. ENVISAT/ASAR Precision Transponders. In CEOS SAR Workshop 1999, Toulouse, Oct. 1999. Keyword(s): Transponders, ASAR, ASAR Transponders, ENVISAT, ENVISAT Transponders.
    Abstract: MPB Technologies Inc. is currently building the Radio Frequency (RF) and control units for a suite of three transponders for the European Space Agency. The transponders are instrumental in the external characterization of the Advanced Synthetic Aperture Radar (ASAR) mounted on board ENVISAT. The prototype transponder was designed and built at ESTEC [1]. This paper presents the operation of the transponders, and describes the final design, integration and testing of the production RF and control transponder units. Like the earlier ERS-1/2 and RADARSAT-1 transponders [2,3], these units provide a constant RCS mode, with constant gain radiometric response, and an azimuth pattern mode to allow for amplitude recording of the satellite pass. In the ASAR transponders, two further modes have been added - a characterization mode to assist in the commissioning and monitoring of ASAR, and an experimental phase-stable mode to provide point target echoes with stabilized phase response.

    @InProceedings{JackSincTam99:ASARTransponders,
    Title = {{ENVISAT/ASAR Precision Transponders}},
    Author = {Harry Jackson and Ian Sinclair and Sebastian Tam},
    Booktitle = {CEOS SAR Workshop 1999},
    Month = {Oct.},
    Url = {http://www.estec.esa.nl/ceos99/papers/p050.pdf},
    Year = {1999},
    Abstract = {MPB Technologies Inc. is currently building the Radio Frequency (RF) and control units for a suite of three transponders for the European Space Agency. The transponders are instrumental in the external characterization of the Advanced Synthetic Aperture Radar (ASAR) mounted on board ENVISAT. The prototype transponder was designed and built at ESTEC [1]. This paper presents the operation of the transponders, and describes the final design, integration and testing of the production RF and control transponder units. Like the earlier ERS-1/2 and RADARSAT-1 transponders [2,3], these units provide a constant RCS mode, with constant gain radiometric response, and an azimuth pattern mode to allow for amplitude recording of the satellite pass. In the ASAR transponders, two further modes have been added - a characterization mode to assist in the commissioning and monitoring of ASAR, and an experimental phase-stable mode to provide point target echoes with stabilized phase response.},
    Address = {Toulouse},
    Day = {26-29},
    Keywords = {Transponders, ASAR, ASAR Transponders, ENVISAT, ENVISAT Transponders},
    Pdf = {../../../docs/JackSincTam99.pdf} 
    }
    


  12. Richard T. Lord and Michael R. Inggs. Efficient RFI Suppression in SAR Using a LMS Adaptive Filter with Sidelobe Suppression Integrated with the Range-Doppler Algorithm. In IGARSS '99, International Geoscience and Remote Sensing Symposium, volume 1, pages 574-576, June 1999. Keyword(s): SAR Processing, RFI Suppression, P-Band, Range-Doppler Algorithm.
    Abstract: The LMS adaptive filter has been used successfully to suppress radio frequency interference (RFI) from SAR images. This paper describes a method to efficiently implement this filter by integrating it with the range-Doppler algorithm. A technique to reduce the sidelobes created by the filter is described and illustrated on simulated data and on real P-band data

    @InProceedings{LordInggs99:RFI,
    Title = {{Efficient RFI Suppression in SAR Using a LMS Adaptive Filter with Sidelobe Suppression Integrated with the Range-Doppler Algorithm}},
    Author = {Richard T. Lord and Michael R. Inggs},
    Booktitle = {IGARSS '99, International Geoscience and Remote Sensing Symposium},
    Month = Jun,
    Pages = {574-576},
    Url = {http://ieeexplore.ieee.org/iel5/6246/16737/00773569.pdf},
    Volume = {1},
    Year = {1999},
    Abstract = {The LMS adaptive filter has been used successfully to suppress radio frequency interference (RFI) from SAR images. This paper describes a method to efficiently implement this filter by integrating it with the range-Doppler algorithm. A technique to reduce the sidelobes created by the filter is described and illustrated on simulated data and on real P-band data},
    Keywords = {SAR Processing, RFI Suppression, P-Band, Range-Doppler Algorithm},
    Pdf = {../../../docs/LordInggs99.pdf} 
    }
    


  13. Andrea Monti-Guarnieri, Fabio Rocca, Pietro Guccione, and Ciro Cafforio. Optimal Interferometric ScanSAR Focusing. In IGARSS '99, International Geoscience and Remote Sensing Symposium, volume 3, pages 1718-1720, 1999. Keyword(s): SAR Processing, Interferometry, ScanSAR, Focusing.
    Abstract: This paper deals with phase preserving focusing for very low resolution ScanSAR. Conventional techniques get ScanSAR focusing by exploiting the SAR matched reference, and compensate scalloping by an inverse antenna weighting. Yet, this approach introduces a space-variant distortion in the focused impulse response (IRF). A rather different focusing technique is then proposed, where the set of space-variant focusing kernels is computed by means of Wiener deconvolution. They perform ScanSAR focusing and descalloping at one time, achieving the finest resolution and without distorting the impulse response.

    @InProceedings{monti01:optInterfFocus,
    Title = {{Optimal Interferometric ScanSAR Focusing}},
    Author = {Andrea Monti-Guarnieri and Fabio Rocca and Pietro Guccione and Ciro Cafforio},
    Booktitle = {IGARSS '99, International Geoscience and Remote Sensing Symposium},
    Pages = {1718-1720},
    Url = {http://ieeexplore.ieee.org/iel5/6246/16741/00772072.pdf},
    Volume = {3},
    Year = {1999},
    Abstract = {This paper deals with phase preserving focusing for very low resolution ScanSAR. Conventional techniques get ScanSAR focusing by exploiting the SAR matched reference, and compensate scalloping by an inverse antenna weighting. Yet, this approach introduces a space-variant distortion in the focused impulse response (IRF). A rather different focusing technique is then proposed, where the set of space-variant focusing kernels is computed by means of Wiener deconvolution. They perform ScanSAR focusing and descalloping at one time, achieving the finest resolution and without distorting the impulse response.},
    Keywords = {SAR Processing, Interferometry, ScanSAR, Focusing},
    Pdf = {../../../docs/optInterfFocusingMonti.pdf} 
    }
    


  14. A. Potsis, A. Reigber, and K.P. Papathanassiou. A phase preserving method for RF interference suppression in P-band. In Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International, volume 5, pages 2655-2657, 1999. Keyword(s): SAR Processing, interference suppression, radar interference, radar theory, radiowave interferometry, synthetic aperture radar, ESAR, P-Band, Airborne SAR, P-band synthetic aperture radar interferometric data, RFI Suppression, Solothurn, Switzerland, interferometric SAR data applications, least mean square method, phase preserving method, phase preserving notch filter, polarimetric interferometric SAR data.
    Abstract: Addresses the least mean square method for estimation and coherent subtraction of the RF interference in interferometric SAR data applications. The authors also compare the results with a phase preserving notch filter. For this purposes the authors use polarimetric interferometric SAR data from a test site in Solothum/Switzerland collected by the DLR's Experimental SAR (ESAR)

    @InProceedings{potsisReigberPapathanassiou99:RFI,
    Title = {A phase preserving method for RF interference suppression in P-band},
    Author = {Potsis, A. and Reigber, A. and Papathanassiou, K.P.},
    Booktitle = {Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International},
    Pages = {2655--2657},
    Url = {http://ieeexplore.ieee.org/iel5/6246/16714/00771607.pdf},
    Volume = {5},
    Year = {1999},
    Abstract = {Addresses the least mean square method for estimation and coherent subtraction of the RF interference in interferometric SAR data applications. The authors also compare the results with a phase preserving notch filter. For this purposes the authors use polarimetric interferometric SAR data from a test site in Solothum/Switzerland collected by the DLR's Experimental SAR (ESAR)},
    Keywords = {SAR Processing, interference suppression, radar interference, radar theory, radiowave interferometry, synthetic aperture radar, ESAR, P-Band, Airborne SAR, P-band synthetic aperture radar interferometric data, RFI Suppression, Solothurn, Switzerland, interferometric SAR data applications, least mean square method, phase preserving method, phase preserving notch filter, polarimetric interferometric SAR data},
    Owner = {ofrey},
    Pdf = {../../../docs/potsisReigberPapathanassiou99.pdf} 
    }
    


  15. Richard Rau and James H. McClellan. Data Efficient Implementation of UWBWA SAR Algorithms. In ICASSP '99, International Conference on Acoustics, Speech, and Signal Processing, volume 6, pages 3525-3528, 1999. Keyword(s): SAR Processing, Back-Projection, Ultra-Wideband SAR, Fan Filter, Quincunx Grid, TDBP, Time-Domain Back-Projection, TDBP.
    Abstract: It is shown that the particular form of the frequency support of raw data and focused imagery obtained from an ultra-wideband, wide beamwidth synthetic aperture radar system can be exploited in nonseparable sampling schemes to reduce the overall amount of raw data samples and image pixels that need to be stored and computed. Furthermore, it is demonstrated that the constant integration angle backprojection (CIAB) image former implicitly applies a fan filter that interpolates raw data sampled on a quincunx grid back onto the underlying rectangular grid. This subtle property of the CIAB has not been exploited so far. It leads to higher quality images with less computational complexity.

    @InProceedings{RauMcClellan99:,
    Title = {{Data Efficient Implementation of UWBWA SAR Algorithms}},
    Author = {Richard Rau and James H. McClellan},
    Booktitle = {ICASSP '99, International Conference on Acoustics, Speech, and Signal Processing},
    Pages = {3525-3528},
    Volume = {6},
    Year = {1999},
    Abstract = {It is shown that the particular form of the frequency support of raw data and focused imagery obtained from an ultra-wideband, wide beamwidth synthetic aperture radar system can be exploited in nonseparable sampling schemes to reduce the overall amount of raw data samples and image pixels that need to be stored and computed. Furthermore, it is demonstrated that the constant integration angle backprojection (CIAB) image former implicitly applies a fan filter that interpolates raw data sampled on a quincunx grid back onto the underlying rectangular grid. This subtle property of the CIAB has not been exploited so far. It leads to higher quality images with less computational complexity.},
    Keywords = {SAR Processing, Back-Projection, Ultra-Wideband SAR, Fan Filter, Quincunx Grid, TDBP, Time-Domain Back-Projection, TDBP},
    Pdf = {../../../docs/rauMcClellan99.pdf} 
    }
    


  16. Z. She, D.A. Gray, R.E. Bogner, and J. Homer. Three-dimensional SAR imaging via multiple pass processing. In Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International, volume 5, pages 2389-2391, 1999. Keyword(s): SAR Processing, SAR Tomography, Tomography, geophysical techniques, radar imaging, remote sensing by radar, spaceborne radar, synthetic aperture radar, terrain mapping, topography (Earth), DFT, InSAR, SAR, SAR image, beamforming, eigenvector method, elevation, geophysical measurement technique, image registration, land surface topography, multiple pass processing, phase correction, radar imaging, radar remote sensing, spaceborne radar, subspace method, superresolution, synthetic aperture radar, terrain mapping, three-dimensional imaging.
    Abstract: This paper develops a novel approach to reconstruct a three-dimensional (3D) SAR image with multiple pass processing. It involves image registration, phase correction and beamforming in elevation. An eigenvector method is proposed for the phase correction and the beamforming in elevation is carried out by a DFT or a subspace method for superresolution. 3D SAR images are demonstrated by processing ERS-1 real data with the proposed approach

    @InProceedings{sheGrayBognerHomer99:Tomo,
    Title = {Three-dimensional SAR imaging via multiple pass processing},
    Author = {She, Z. and Gray, D.A. and Bogner, R.E. and Homer, J.},
    Booktitle = {Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International},
    Pages = {2389--2391},
    Url = {http://ieeexplore.ieee.org/iel5/6246/16714/00771519.pdf},
    Volume = {5},
    Year = {1999},
    Abstract = {This paper develops a novel approach to reconstruct a three-dimensional (3D) SAR image with multiple pass processing. It involves image registration, phase correction and beamforming in elevation. An eigenvector method is proposed for the phase correction and the beamforming in elevation is carried out by a DFT or a subspace method for superresolution. 3D SAR images are demonstrated by processing ERS-1 real data with the proposed approach},
    Keywords = {SAR Processing, SAR Tomography, Tomography, geophysical techniques, radar imaging, remote sensing by radar, spaceborne radar, synthetic aperture radar, terrain mapping, topography (Earth), DFT, InSAR, SAR, SAR image, beamforming, eigenvector method, elevation, geophysical measurement technique, image registration, land surface topography, multiple pass processing, phase correction, radar imaging, radar remote sensing, spaceborne radar, subspace method, superresolution, synthetic aperture radar, terrain mapping, three-dimensional imaging},
    Owner = {ofrey},
    Pdf = {../../../docs/sheGrayBognerHomerTomo99.pdf} 
    }
    


  17. D.G. Thompson, J.S. Bates, and D.V. Arnold. Extending the phase gradient autofocus algorithm for low-altitude stripmap mode SAR. In The Record of the 1999 IEEE Radar Conference, pages 36-40, April 1999. Keyword(s): SAR Processing, Autofocus, Phase Gradient Autofocus, Strip-map, Range-Dependent.
    @InProceedings{thompsonBatesArnold1999a:PGA,
    Title = {Extending the phase gradient autofocus algorithm for low-altitude stripmap mode SAR},
    Author = {Thompson, D.G. and Bates, J.S. and Arnold, D.V.},
    Booktitle = {The Record of the 1999 IEEE Radar Conference},
    Doi = {10.1109/NRC.1999.767199},
    Month = {apr},
    Pages = {36--40},
    Url = {http://ieeexplore.ieee.org/iel5/6212/16591/00767199.pdf},
    Year = {1999},
    Keywords = {SAR Processing, Autofocus, Phase Gradient Autofocus, Strip-map, Range-Dependent},
    Owner = {ofrey},
    Pdf = {../../../docs/thompsonBatesArnold1999a.pdf} 
    }
    


  18. D.G. Thompson, J.S. Bates, D.V. Arnold, and David G. Long. Extending the phase gradient autofocus algorithm for low-altitude stripmap mode SAR. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS '99, volume 1, pages 564-566, July 1999. Keyword(s): SAR Processing, Autofocus, Phase Gradient Autofocus, Strip-map, Range-dependent.
    @InProceedings{thompsonBatesArnold1999b:PGA,
    Title = {Extending the phase gradient autofocus algorithm for low-altitude stripmap mode SAR},
    Author = {Thompson, D.G. and Bates, J.S. and Arnold, D.V. and Long, David G.},
    Booktitle = {IEEE International Geoscience and Remote Sensing Symposium, IGARSS '99},
    Doi = {10.1109/IGARSS.1999.773566},
    Month = jul,
    Pages = {564--566},
    Url = {http://ieeexplore.ieee.org/iel5/6246/16737/00773566.pdf},
    Volume = {1},
    Year = {1999},
    Keywords = {SAR Processing, Autofocus, Phase Gradient Autofocus, Strip-map, Range-dependent},
    Owner = {ofrey},
    Pdf = {../../../docs/thompsonBatesArnold1999b.pdf} 
    }
    


  19. P. Tsakalides and C.L. Nikus. A new phase gradient autofocus technique for high resolution image formation based on fractional lower-order statistics. In Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference on, volume 2, pages 667-670, September 1999. Keyword(s): SAR Processing, Autofocus, Phase Gradient Autofocus.
    @InProceedings{Tsakalides1999,
    Title = {A new phase gradient autofocus technique for high resolution image formation based on fractional lower-order statistics},
    Author = {Tsakalides, P. and Nikus, C.L.},
    Booktitle = {Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference on},
    Doi = {10.1109/ICECS.1999.813195},
    Month = sep,
    Pages = {667--670},
    Volume = {2},
    Year = {1999},
    Keywords = {SAR Processing, Autofocus, Phase Gradient Autofocus},
    Owner = {ofrey} 
    }
    


  20. Lars M. H. Ulander and Per-Olov Frölind. Precision Processing of CARABAS HF/VHF-Band SAR Data. In IGARSS '99, International Geoscience and Remote Sensing Symposium, volume 1, pages 47-49, June 1999. Keyword(s): SAR Processing, RFI Suppression, Back-Projection, Time-Domain Back-Projection, TDBP, Ultra-Wideband SAR, VHF SAR, CARABAS, Airborne SAR, Motion Compensation.
    Abstract: A stream-lined precision processor has been developed for the CARABAS-II HF/VHF-band SAR system. The authors describe the basic system characteristics, the normal waveform used, and the signal processing techniques to form images. In particular, challenges related to the stepped-frequency waveform, the radio-frequency interference environment, and widebeam motion-compensation are discussed and processing solutions are devised.

    @InProceedings{UlanderForlind99:RFI,
    Title = {{Precision Processing of CARABAS HF/VHF-Band SAR Data}},
    Author = {Lars M. H. Ulander and Per-Olov Fr{\"o}lind},
    Booktitle = {IGARSS '99, International Geoscience and Remote Sensing Symposium},
    Month = Jun,
    Pages = {47-49},
    Url = {http://ieeexplore.ieee.org/iel5/6246/16737/00773396.pdf},
    Volume = {1},
    Year = {1999},
    Abstract = {A stream-lined precision processor has been developed for the CARABAS-II HF/VHF-band SAR system. The authors describe the basic system characteristics, the normal waveform used, and the signal processing techniques to form images. In particular, challenges related to the stepped-frequency waveform, the radio-frequency interference environment, and widebeam motion-compensation are discussed and processing solutions are devised.},
    Keywords = {SAR Processing, RFI Suppression, Back-Projection, Time-Domain Back-Projection, TDBP, Ultra-Wideband SAR, VHF SAR, CARABAS, Airborne SAR, Motion Compensation},
    Pdf = {../../../docs/UlanderForlind99.pdf} 
    }
    


  21. Urs Wegmuller. Automated terrain corrected SAR geocoding. In Proc. IEEE Int. Geosci. Remote Sens. Symp., volume 3, pages 1712-1714, 1999. Keyword(s): SAR, SAR intensity image, automated terrain corrected method, cross-correlation, digital elevation model, geocoding, geocoding transformation, geophysical measurement technique, image coding, land surface, radar imaging, radar remote sensing, synthetic aperture radar, terrain mapping, geophysical signal processing, geophysical techniques, image coding, radar imaging, remote sensing by radar, synthetic aperture radar, terrain mapping.
    Abstract: A technique for automated terrain corrected SAR geocoding is presented. Instead of operator selected control points the presented method uses cross-correlation with a SAR intensity image simulated from the digital elevation model to refine the geocoding transformation

    @InProceedings{wegmuller1999:TerrainGeocoding,
    Title = {Automated terrain corrected {SAR} geocoding},
    Author = {Wegmuller, Urs},
    Booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    Doi = {10.1109/IGARSS.1999.772070},
    Pages = {1712-1714},
    Url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=772070},
    Volume = {3},
    Year = {1999},
    Abstract = {A technique for automated terrain corrected SAR geocoding is presented. Instead of operator selected control points the presented method uses cross-correlation with a SAR intensity image simulated from the digital elevation model to refine the geocoding transformation},
    Keywords = {SAR;SAR intensity image;automated terrain corrected method;cross-correlation;digital elevation model;geocoding;geocoding transformation;geophysical measurement technique;image coding;land surface;radar imaging;radar remote sensing;synthetic aperture radar;terrain mapping;geophysical signal processing;geophysical techniques;image coding;radar imaging;remote sensing by radar;synthetic aperture radar;terrain mapping},
    Owner = {ofrey},
    Pdf = {../../../docs/wegmuller1999.pdf} 
    }
    


  22. Ali F. Yegulalp. Fast Backprojection Algorithm for Synthetic Aperture Radar. In The Record of the 1999 IEEE Radar Conference, pages 60-65, 1999. Keyword(s): SAR Processing, Back-Projection, Convolution Back-Projection, FOPEN, Ultra-Wideband SAR, Image Formation, Focusing, Motion Compensation, Time-Domain Back-Projection, TDBP.
    Abstract: We introduce a new algorithm for time-domain backprojection of synthetic aperture radar (SAR) data. The algorithm reproduces images generated by standard backprojection pixel-for-pixel to any required tolerance, but it runs roughly ?N times faster for an N by N pixel image. Fast backprojection retains the advantages of standard backprojection: perfect motion compensation for any flight path, low artifact levels, unlimited scene size, perfect focus for arbitrarily wide bandwidths and integration angles, and strictly local processing (i.e., pulses can be processed as they are collected without along-track buffering or corner turns). The new algorithm also makes it possible to store the image in progress on disk (rather than in memory) with only a mild penalty in processing speed.

    @InProceedings{yegulalp:fourier,
    Title = {{Fast Backprojection Algorithm for Synthetic Aperture Radar}},
    Author = {Ali F. Yegulalp},
    Booktitle = {The Record of the 1999 IEEE Radar Conference},
    Pages = {60-65},
    Url = {http://ieeexplore.ieee.org/iel5/6212/16591/00767270.pdf},
    Year = {1999},
    Abstract = {We introduce a new algorithm for time-domain backprojection of synthetic aperture radar (SAR) data. The algorithm reproduces images generated by standard backprojection pixel-for-pixel to any required tolerance, but it runs roughly ?N times faster for an N by N pixel image. Fast backprojection retains the advantages of standard backprojection: perfect motion compensation for any flight path, low artifact levels, unlimited scene size, perfect focus for arbitrarily wide bandwidths and integration angles, and strictly local processing (i.e., pulses can be processed as they are collected without along-track buffering or corner turns). The new algorithm also makes it possible to store the image in progress on disk (rather than in memory) with only a mild penalty in processing speed.},
    Keywords = {SAR Processing, Back-Projection, Convolution Back-Projection, FOPEN, Ultra-Wideband SAR, Image Formation, Focusing, Motion Compensation, Time-Domain Back-Projection, TDBP},
    Pdf = {../../../docs/yegulalp99.pdf} 
    }
    


  23. P. Zavattero. Distributed target SAR image de-blurring using phase gradient autofocus. In Radar Conference, 1999. The Record of the 1999 IEEE, pages 246-249, April 1999. Keyword(s): SAR Processing, Autofocus, Phase Gradient Autofocus.
    Abstract: A new analysis of errors in blur function estimate formed by the real-time Phase Gradient Autofocus (PGA) algorithm is presented for synthetic aperture radar images of distributed targets in correlated noise clutter. It is shown that the PGA algorithm, like the Attia-Steinberg and Vachon-Raney focusing algorithms, can estimate a translation-invariant blur function when no point reflectors are present. The analysis shows that simulation evaluations of PGA performance which do not include sufficient simulated clutter can tend to underestimate the performance of the algorithm in initial iterations. Implications of the error analysis for performance optimization of real-time PGA implementations are presented for the algorithm steps that involve range bin selection, circular shifting, and windowing. It is shown that range bins selected for processing should be widely spaced if possible. If distributed targets are present which cause locally spatially correlated imagery, then it is desirable that the circular shifting segment of the algorithm maintain maximum decorrelation of the intermediate windowed and aligned images used for iterative phase error estimation.

    @InProceedings{Zavattero1999,
    Title = {Distributed target SAR image de-blurring using phase gradient autofocus},
    Author = {Zavattero, P.},
    Booktitle = {Radar Conference, 1999. The Record of the 1999 IEEE},
    Month = apr,
    Pages = {246--249},
    Year = {1999},
    Abstract = {A new analysis of errors in blur function estimate formed by the real-time Phase Gradient Autofocus (PGA) algorithm is presented for synthetic aperture radar images of distributed targets in correlated noise clutter. It is shown that the PGA algorithm, like the Attia-Steinberg and Vachon-Raney focusing algorithms, can estimate a translation-invariant blur function when no point reflectors are present. The analysis shows that simulation evaluations of PGA performance which do not include sufficient simulated clutter can tend to underestimate the performance of the algorithm in initial iterations. Implications of the error analysis for performance optimization of real-time PGA implementations are presented for the algorithm steps that involve range bin selection, circular shifting, and windowing. It is shown that range bins selected for processing should be widely spaced if possible. If distributed targets are present which cause locally spatially correlated imagery, then it is desirable that the circular shifting segment of the algorithm maintain maximum decorrelation of the intermediate windowed and aligned images used for iterative phase error estimation.},
    Keywords = {SAR Processing, Autofocus, Phase Gradient Autofocus},
    Owner = {ofrey},
    Pdf = {../../../docs/zavattero99.pdf} 
    }
    


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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: Mon Feb 1 16:39:00 2021
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .


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