A REGULARIZED FOCUSS METHOD FOR RADAR FORWARD-LOOKING IMAGING

被引：0
|
作者：
Tuo, Xingyu [1 ]
Wu, Shang [1 ]
Zhang, Yin [1 ]
Cai, Xiaochun [1 ]
Huang, Yulin [1 ]
Yang, Jianyu [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu, Peoples R China
来源：
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
基金：
中国国家自然科学基金;
关键词：
forward-looking imaging; sparse characteristics; regularized FOCUSS; SUPERRESOLUTION;
D O I：
10.1109/IGARSS46834.2022.9884941
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Exploiting the sparse property of the target of interest to achieve super-resolution imaging has been applied to real aperture radar (RAR) forward-looking imaging field. In this paper, we proposed a regularized FOCUSS method to realize RAR forward-looking super-resolution imaging. In addition, we discussed the influence of initialization on the imaging result, and selected the most suitable initialization for RAR forward-looking super-resolution imaging. Compared with the traditional sparse method based on Majorize-Minimization, our proposed algorithm has faster convergence speed under the same parameters condition.
引用
收藏
页码：7685 / 7688
页数：4
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