A Novel SAR Imaging Algorithm Based on Modified Multiple Measurement Vectors Model
CHEN Yichang① ZHANG Qun①② YANG Ting③④ LUO Ying①
①(Institute of Information and Navigation, Air Force Engineering University, Xi’an, 710077, China) ②(Key Laboratory for Information Science of Electromagnetic Waves, Fudan University, Shanghai 200433, China) ③(Huangpi Officer School, Air Force Early-warning Academy, Wuhan 430000, China) ④(The 95133 Army of Chinese People’s Liberation Army, Wuhan 430000, China)
Recently, the Compressed Sensing (CS) theory becomes the researching hot point in SAR imaging. The Multiple Measurement Vectors (MMV) model of CS theory can be used to effectively represent the jointly sparse signals, and it can obtain better performance than Single Measurement Vector (SMV) model. Because the SAR range profiles at different pulses have different sparse structures, which result in the MMV model can not be directly used in the scenario of synthetic aperture radar imaging. In this paper, a modified MMV model is proposed for SAR imaging, and the Range Migration (RM) effect is embedded into the proposed model. Correspondingly, a modified Orthogonal Matching Pursuit (OMP) algorithm is developed to obtain the high-resolution range profile. Experiments based on simulated and measured data demonstrate the validity of the proposed model and the algorithm.
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