Junjun Xiong, Hongqiang Zhang, Hong Hong, Heng Zhao, Xiaohua Zhu, Changzhi Li
{"title":"Multi-target Vital Signs Detection Using SIMO Continuous-wave Radar with DBF Technique","authors":"Junjun Xiong, Hongqiang Zhang, Hong Hong, Heng Zhao, Xiaohua Zhu, Changzhi Li","doi":"10.1109/RWS45077.2020.9050054","DOIUrl":null,"url":null,"abstract":"In this paper, a single-input multiple-output (SIMO) CW radar with digital beam forming (DBF) technique is presented to achieve multi-target vital signs detection. The developed system utilizes eight antennas to capture the reflected signals. Then, the DBF technique is applied to steer the beam towards the subject of interest. As a result, other subjects’ signals can be suppressed. Finally, the time domain vital signs waveform of each subject is obtained. The experimental results show good detection accuracy compared with the reference sensor, which demonstrates the feasibility of the developed system for multi-target vital signs detection.","PeriodicalId":184822,"journal":{"name":"2020 IEEE Radio and Wireless Symposium (RWS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Radio and Wireless Symposium (RWS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RWS45077.2020.9050054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In this paper, a single-input multiple-output (SIMO) CW radar with digital beam forming (DBF) technique is presented to achieve multi-target vital signs detection. The developed system utilizes eight antennas to capture the reflected signals. Then, the DBF technique is applied to steer the beam towards the subject of interest. As a result, other subjects’ signals can be suppressed. Finally, the time domain vital signs waveform of each subject is obtained. The experimental results show good detection accuracy compared with the reference sensor, which demonstrates the feasibility of the developed system for multi-target vital signs detection.