Joint Matrix Form SAR Imaging and Autofocus Based on Compressed Sensing
BU Hong-xia1, BAI Xia2, ZHAO Juan2, QI Yao-hui1, YAN Ruo-ying1
1. College of Physics Science and Information Engineering, Hebei Normal University, Shijiazhuang, Hebei 050024, China;
2. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Compressed sensing (CS) has been successfully applied to the synthetic aperture radar (SAR) imaging.These CS-based SAR imaging algorithms generally assume that the model of the imaging system is accurate.However,in practice it is common to encounter model errors which usually introduce unknown phase errors into the acquired data.The phase errors may cause range migration or defocusing.In this paper,an approach for matrix form joint CS-SAR imaging and autofocus is proposed.Based on smoothed l0 norm (SL0) algorithm,we develop a matrix form regularized SL0 (MRSL0) algorithm to efficiently perform CS-SAR imaging.The MRSL0 adopts inequality constrain to tolerate phase errors and has fast computation speed due to its matrix form.Experiment results demonstrate that the proposed approach can efficiently reconstruct high quality images using limited amount of measurements.
卜红霞, 白霞, 赵娟, 齐耀辉, 闫若颖. 基于压缩感知的矩阵型联合SAR成像与自聚焦算法[J]. 电子学报, 2017, 45(4): 874-881.
BU Hong-xia, BAI Xia, ZHAO Juan, QI Yao-hui, YAN Ruo-ying. Joint Matrix Form SAR Imaging and Autofocus Based on Compressed Sensing. Acta Electronica Sinica, 2017, 45(4): 874-881.
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2017, Vol. 45 
