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Open AccessArticle

An Accurate Method to Distinguish Between Stationary Human and Dog Targets Under Through-Wall Condition Using UWB Radar

Department of Medical Electronics, School of Biomedical Engineering, Fourth Military Medical University, Xi’an 710032, China
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Remote Sens. 2019, 11(21), 2571; https://doi.org/10.3390/rs11212571
Received: 27 September 2019 / Revised: 25 October 2019 / Accepted: 30 October 2019 / Published: 1 November 2019
(This article belongs to the Special Issue Radar Remote Sensing on Life Activities)
Research work on distinguishing humans from animals can help provide priority orders and optimize the distribution of resources in earthquake- or mining-related rescue missions. However, the existing solutions are few and their stability and accuracy of classification are less. This study proposes an accurate method for distinguishing stationary human targets from dog targets under through-wall condition based on ultra-wideband (UWB) radar. Eight humans and five beagles were used to collect 130 samples of through-wall signals using the UWB radar. Twelve corresponding features belonging to four categories were combined using the support vector machine (SVM) method. A recursive feature elimination (RFE) method determined an optimal feature subset from the twelve features to overcome overfitting and poor generalization. The results after ten-fold cross-validation showed that the area under the receiver operator characteristic (ROC) curve can reach 0.9993, which indicates that the two subjects can be distinguished under through-wall condition. The study also compared the ability of the proposed features of four categories when used independently in a classifier. Comparison results indicated that wavelet entropy-corresponding features among them have the best performance. The method and results are envisioned to be applied in various practical situations, such as post-disaster searching, hostage rescues, and intelligent homecare. View Full-Text
Keywords: UWB radar; distinguishing human targets from dog targets; SVM; wavelet entropy-corresponding features UWB radar; distinguishing human targets from dog targets; SVM; wavelet entropy-corresponding features
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MDPI and ACS Style

Ma, Y.; Liang, F.; Wang, P.; Lv, H.; Yu, X.; Zhang, Y.; Wang, J. An Accurate Method to Distinguish Between Stationary Human and Dog Targets Under Through-Wall Condition Using UWB Radar. Remote Sens. 2019, 11, 2571.

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