Dataset of human motion status using IR-UWB through-wall radar

作     者：ZHU Zhengliang YANG Degui ZHANG Junchao TONG Feng ZHU Zhengliang;YANG Degui;ZHANG Junchao;TONG Feng

作者机构：Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Ministry of EducationXia-men UniversityXiamen 361005China School of Aeronautics and AstronauticsCentral South UniversityChangsha 410083China College of Ocean and Earth SciencesXiamen UniversityXiamen 361005China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2021年第32卷第5期

页      面：1083-1096页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

基　　金：This work was supported by the National Key Research and Development Program of China(2018YFC0810202) the National Defence Pre-research Foundation of China(61404130119) 

主　　题：impulse radio ultra-wideband(IR-UWB) through-wall radar human motion status dataset convolutional neural network(CNN) 

摘      要：Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and *** the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at *** many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the *** published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar *** test subjects are measured in different environments and several defined motion *** the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are *** the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple ***,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.