Processing of Bistatic SAR Data With Nonlinear Trajectory Using a Controlled-SVD Algorithm

The nonlinear trajectory and bistatic characteristics of general bistatic synthetic aperture radar (SAR) can cause severe two-dimensional space-variance in the echo signal, and therefore it is difficult to focus the echo signal directly using the traditional frequency-domain imaging algorithm based...

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Bibliographic Details
Published in:IEEE journal of selected topics in applied earth observations and remote sensing 2021, Vol.14, p.5750-5759
Main Authors: Xiong, Yi, Liang, Buge, Yu, Hanwen, Chen, Jianlai, Jin, Yanghao, Xing, Mengdao
Format: Article
Language:English
Subjects:
Algorithms
Azimuth
Bastatic
Echoes
Image quality
Imaging techniques
Interpolation
nonlinear trajectory
Radar imaging
SAR (radar)
Scaling
Signal processing algorithms
Singular value decomposition
singular value decomposition (SVD)
Synthetic aperture radar
synthetic aperture radar (SAR)
Trajectory
Trajectory control
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Summary:The nonlinear trajectory and bistatic characteristics of general bistatic synthetic aperture radar (SAR) can cause severe two-dimensional space-variance in the echo signal, and therefore it is difficult to focus the echo signal directly using the traditional frequency-domain imaging algorithm based on the assumption of azimuth translational invariance. At present, the state-of-the-art nonlinear trajectory imaging algorithm is based on singular value decomposition (SVD), which has the problem that SVD may be not controlled, and thus may lead to a high imaging complexity or low imaging accuracy. Therefore, this article proposes a nonlinear trajectory SAR imaging algorithm based on controlled SVD (CSVD). First, the chirp scaling algorithm is used to correct the range space-variance, and then SVD is used to decompose the remaining azimuth space-variant phase, and the first two feature components after SVD are integrated to make them be represented by a new feature component. Finally, the new feature component is used for interpolation to correct the azimuth space-variance. The simulation results show that the proposed CSVD can further improve the image quality compared with SVD-Stolt.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2021.3084619