Jiang Cheng-long①②③ Zhang Bing-chen①② Wang Zheng-dao④ Hong Wen①②
①(Science and Technology on Microwave Imaging Laboratory, Beijing 100190, China) ②(Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China) ③(University of Chinese Academy of Sciences, Beijing 100049, China) ④(Iowa State University, USA)
Conventional matched filtering based algorithms are not sufficiently good at dealing with the anisotropic backscattering behavior of targets in Wide Angle SAR (WASAR) imaging. Sparse signal processing provides a new idea for this problem, the anisotropic problem is modeled as a group of under-determined linear equations. However, the scale of unknowns in the under-determined equations is in linear order of the number of the observation angle. As the observation angle increases, the anisotropic problem becomes more and more difficult to be solved, even failed for conventional sparse signal processing algorithms. This paper presents a Group- sparse Complex Approximated Message Passing (GCAMP) algorithm for WASAR imaging. Firstly, a group sparse based WASAR imaging model is provided according to the structured property of backscattering coefficients across different observation angles. Secondly, the GCAMP algorithm is derived from the imaging model using message passing theory. Results of simulation demonstrate the effectiveness of the proposed algorithm.
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