A SAR imaging method based on generalized minimax-concave penalty

作     者：Zhonghao WEI Bingchen ZHANG Yirong WU 

作者机构：University of Chinese Academy of Sciences Key Laboratory of Technology in Geospatial Information Processing and Application SystemsInstitute of Electronics Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2019年第62卷第2期

页      面：233-239页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

基　　金：supported by National Natural Science Foundation of China (Grant No. 61571419) 

主　　题：SAR A SAR imaging method based on generalized minimax-concave penalty 

摘      要：Dear editor,Sparse signal processing offers a framework for synthetic aperture radar （SAR） imaging [1, 2]. As an efficient tool in sparse signal processing, L1minimization is often used in the reconstruction of SAR images. When implemented in SAR imaging [3–5], L1minimization offers significant improvement in the properties by suppressing the sidelobes and clutter. However, L1minimization is known to be a biased estimator. The L1minimization based algorithms such as the iterative