Fast Factorized Backprojection Imaging Algorithm Integrated With Motion Trajectory Estimation for Bistatic Forward-Looking SAR

被引:34
|
作者
Pu, Wei [1 ]
Wu, Junjie [2 ]
Huang, Yulin [2 ]
Yang, Jianyu [2 ]
Yang, Haiguang [2 ]
机构
[1] UCL, Dept Elect & Elect Engn, London WC1E 6BT, England
[2] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Bistatic forward-looking synthetic aperture radar (BFSAR); fast factorized back-projection (FFBP); motion trajectory estimation; APERTURE RADAR AUTOFOCUS; HIGH-RESOLUTION; BACK-PROJECTION; FFBP ALGORITHM; DESCENT METHOD; AIRBORNE SAR; COMPENSATION; APPROXIMATION; OPTIMIZATION; CONVERGENCE;
D O I
10.1109/JSTARS.2019.2945118
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A bistatic forward-looking synthetic aperture radar (BFSAR) is increasingly in the focus of study, as it breaks through the limitations of imaging on a forward-looking terrain of a moving platform. Fast factorized backprojection (FFBP) is a reliable BFSAR imaging algorithm, with both imaging precision and efficiency being taken into consideration. In FFBP imaging, compensation of the motion errors is important to obtain a well-focused image. To accomplish an accurate motion compensation in image processing, a high-precision navigation system is needed. However, in many cases, because of the accuracy limit of such systems, motion errors are difficult to be compensated correctly, resulting chiefly in resolution decrease in the final images. To deal with such a problem, we propose an FFBP imaging algorithm integrated with motion trajectory estimation for BFSAR. First, a coarse-to-fine residual range cell migration (RCM) correction scheme is applied to ensure the residual RCM within a range resolution. Then, an optimization model with respect to motion trajectory estimation under the criterion of maximum image sharpness is built during FFBP imaging. According to the coarse-to-fine residual RCM correction scheme and the motion trajectory estimation model, a block coordinate descent technique based on steepest descent optimization method integrated with residual RCM correction is proposed to estimate the motion errors in FFBP imaging. We empirically compare the proposed method with several state-of-the-art BFSAR imaging and autofocus algorithms. Simulations on BFSAR data show that the proposed method is more accurate and has similar computational cost.
引用
收藏
页码:3949 / 3965
页数:17
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