SUPER-RESOLUTION OF FORWARD-LOOKING SCANNING RADAR BASED ON LOW-RANK AND SPARSE CONSTRAINTS

被引：0
|
作者：
Zhang, Wentao [1 ]
Li, Wenchao [1 ]
Zhang, Yongchao [1 ]
Zhang, Yin [1 ]
Huang, Yulin [1 ]
Yang, Jianyu [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu, Sichuan, Peoples R China
来源：
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
Forward-looking scanning radar; super-resolution; low-rank and sparse constraints;
D O I：
10.1109/igarss.2019.8898374
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Regularization technology can be utilized to improve the azimuth resolution for forward-looking scanning radar. In this paper, low-rank and sparse constraints as regularization norms are incorporated into the forward-looking scanning radar imaging. This method can achieve azimuth super-resolution and noise suppression. Simulations are given to verify the effectiveness of the method.
引用
收藏
页码：2758 / 2761
页数：4
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