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Sensors 2016, 16(9), 1409; doi:10.3390/s16091409

Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection

1
Department of Electronics and Computer Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Korea
2
MOMED Solution, Gwangju 61008, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Changzhi Li
Received: 17 June 2016 / Revised: 15 August 2016 / Accepted: 26 August 2016 / Published: 1 September 2016
(This article belongs to the Special Issue Non-Contact Sensing)
View Full-Text   |   Download PDF [2399 KB, uploaded 1 September 2016]   |  

Abstract

The detection of a moving target using an IR-UWB Radar involves the core task of separating the waves reflected by the static background and by the moving target. This paper investigates the capacity of the low-rank and sparse matrix decomposition approach to separate the background and the foreground in the trend of UWB Radar-based moving target detection. Robust PCA models are criticized for being batched-data-oriented, which makes them inconvenient in realistic environments where frames need to be processed as they are recorded in real time. In this paper, a novel method based on overlapping-windows processing is proposed to cope with online processing. The method consists of processing a small batch of frames which will be continually updated without changing its size as new frames are captured. We prove that RPCA (via its Inexact Augmented Lagrange Multiplier (IALM) model) can successfully separate the two subspaces, which enhances the accuracy of target detection. The overlapping-windows processing method converges on the optimal solution with its batch counterpart (i.e., processing batched data with RPCA), and both methods prove the robustness and efficiency of the RPCA over the classic PCA and the commonly used exponential averaging method. View Full-Text
Keywords: UWB; moving target detection; background subtraction; matrix decomposition; low-rank; sparse; RPCA; augmented Lagrange multiplier; online processing; real-time processing UWB; moving target detection; background subtraction; matrix decomposition; low-rank; sparse; RPCA; augmented Lagrange multiplier; online processing; real-time processing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sabushimike, D.; Na, S.Y.; Kim, J.Y.; Bui, N.N.; Seo, K.S.; Kim, G.G. Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection. Sensors 2016, 16, 1409.

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