The Multi-domain Union Clutter Suppression Algorithm Based on Robust Principal Component Analysis

被引：1

作者：

Li Xiangping ^{[1
]}

Wang Mingze ^{[1
]}

Dan Bo ^{[1
]}

Li Wei ^{[2
]}

Ma Junwei ^{[3
]}

机构：

[1] Naval Aviat Univ, Coast Guard Coll, Yantai 264001, Peoples R China

[2] Naval Aviat Univ, Air Combat Serv Coll, Yantai 264001, Peoples R China

[3] Naval Aviat Univ, Aviat Support Profess Training Base, Qingdao 266109, Peoples R China

来源：

JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY | 2022年 / 44卷 / 04期

关键词：

Through-the-Wall Imaging Radar (TWIR); Clutter suppression; Robust Principal Component Analysis (RPCA); Joint low-rank and sparse model; Multi-domain union; LOW-RANK;

D O I：

10.11999/JEIT210676

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In through-the-wall imaging, the clutter can not be eliminated completely through traditional algorithms, and affects seriously the subsequent target detection and recognition. To solve the problem, based on robust principal component analysis theory, a joint low-rank and sparse model is established in echo and image domain respectively. The models are solved by Smoothing Fast Alternating Linearization (SFAL) method. Then, the target images are dealt with exponentially weighted multiply multi-domain image fusion to obtain the final image. The simulation results indicate that the algorithm has great speed and accuracy with effective improvement on imaging quality of targets.

引用

页码：1303 / 1310

页数：8

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