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Detection of Multiple Stationary Humans Using UWB MIMO Radar

Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In...

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Autores principales: Liang, Fulai, Qi, Fugui, An, Qiang, Lv, Hao, Chen, Fuming, Li, Zhao, Wang, Jianqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134581/
https://www.ncbi.nlm.nih.gov/pubmed/27854356
http://dx.doi.org/10.3390/s16111922
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author Liang, Fulai
Qi, Fugui
An, Qiang
Lv, Hao
Chen, Fuming
Li, Zhao
Wang, Jianqi
author_facet Liang, Fulai
Qi, Fugui
An, Qiang
Lv, Hao
Chen, Fuming
Li, Zhao
Wang, Jianqi
author_sort Liang, Fulai
collection PubMed
description Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls.
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spelling pubmed-51345812017-01-03 Detection of Multiple Stationary Humans Using UWB MIMO Radar Liang, Fulai Qi, Fugui An, Qiang Lv, Hao Chen, Fuming Li, Zhao Wang, Jianqi Sensors (Basel) Article Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls. MDPI 2016-11-16 /pmc/articles/PMC5134581/ /pubmed/27854356 http://dx.doi.org/10.3390/s16111922 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liang, Fulai
Qi, Fugui
An, Qiang
Lv, Hao
Chen, Fuming
Li, Zhao
Wang, Jianqi
Detection of Multiple Stationary Humans Using UWB MIMO Radar
title Detection of Multiple Stationary Humans Using UWB MIMO Radar
title_full Detection of Multiple Stationary Humans Using UWB MIMO Radar
title_fullStr Detection of Multiple Stationary Humans Using UWB MIMO Radar
title_full_unstemmed Detection of Multiple Stationary Humans Using UWB MIMO Radar
title_short Detection of Multiple Stationary Humans Using UWB MIMO Radar
title_sort detection of multiple stationary humans using uwb mimo radar
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134581/
https://www.ncbi.nlm.nih.gov/pubmed/27854356
http://dx.doi.org/10.3390/s16111922
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