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

作     者：Xiong, Yi Liang, Buge Yu, Hanwen Chen, Jianlai Jin, Yanghao Xing, Mengdao 

作者机构：Cent South Univ Sch Automat Changsha 410083 Peoples R China Cent South Univ Sch Aeronaut & Astronaut Changsha 410083 Peoples R China Univ Elect Sci & Technol China Sch Resources & Environm Chengdu 611731 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China 

出 版 物：《IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING》 (IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.)

年 卷 期：2021年第14卷

页      面：5750-5759页

核心收录：

学科分类：0808[工学-电气工程] 1002[医学-临床医学] 08[工学] 0705[理学-地理学] 0816[工学-测绘科学与技术] 

基　　金：National Natural Science Foundation of China National Key Research and Development Program of China [2018YFC081020204] 

主　　题：Azimuth Radar imaging Interpolation Signal processing algorithms Trajectory Synthetic aperture radar Transmitters Bastatic nonlinear trajectory singular value decomposition (SVD) synthetic aperture radar (SAR) 

摘      要：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.