Wall clutter mitigation for radar imaging of indoor targets: A matrix completion approach

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Abstract

This paper presents a low-rank matrix completion approach to tackle the problem of wall clutter mitigation for through-wall radar imaging in the compressive sensing context. In particular, the task of wall clutter removal is reformulated as a matrix completion problem in which a low-rank matrix containing wall clutter is reconstructed from compressive measurements. The proposed model regularizes the low-rank prior of the wall-clutter matrix via the nuclear norm, casting the wall-clutter mitigation task as a nuclear-norm penalized least squares problem. To solve this optimization problem, an iterative algorithm based on proximal gradient technique is introduced. Experiments on simulated full-wave electromagnetic data are conducted under compressive sensing scenarios. The results show that the proposed matrix completion approach is very effective at suppressing unwanted wall clutter and enhancing the desired targets.

Original languageEnglish
Title of host publicationProceedings - 2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems, IES 2017
EditorsHuynh Thi Thanh Binh, Yew Soon Ong, Lam Thu Bui, Van-Giang Nguyen, Akira Namatame, Trung Thanh Nguyen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages116-121
Number of pages6
ISBN (Electronic)9781538607435
DOIs
Publication statusPublished - 21 Dec 2017
Event21st Asia Pacific Symposium on Intelligent and Evolutionary Systems, IES 2017 - Hanoi, Viet Nam
Duration: 15 Nov 201717 Nov 2017

Publication series

NameProceedings - 2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems, IES 2017
Volume2017-January

Conference

Conference21st Asia Pacific Symposium on Intelligent and Evolutionary Systems, IES 2017
Country/TerritoryViet Nam
CityHanoi
Period15/11/1717/11/17

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