title: Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.
abstract: Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.
authors: Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China. zyfmmu@126.com.|Center for Disease Control and Prevention of Guangzhou Military Region, Guangzhou 510507, China. zyfmmu@126.com.
authors: Yang
authors: Y
authors: Zhang
authors: Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China. cfm5762@126.com.
authors: Fuming
authors: F
authors: Chen
authors: Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China. xinyin20130419@163.com.
authors: Huijun
authors: H
authors: Xue
authors: Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China. lizhaofmmu@fmmu.edu.cn.
authors: Zhao
authors: Z
authors: Li
authors: Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China. anqiang900903@163.com.
authors: Qiang
authors: Q
authors: An
authors: Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China. wangjq@fmmu.edu.cn.
authors: Jianqi
authors: J
authors: Wang
authors: Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China. yangzhang@fmmu.edu.cn.
authors: Yang
authors: Y
authors: Zhang
mesh_terms: D000465:Algorithms; D006801:Humans; D009068:Movement / Q000502:physiology*; D011825:Radar / Q000295:instrumentation; D012119:Respiration; D012815:Signal Processing, Computer-Assisted; D013816:Thermodynamics
keywords: cross-correlation; energy detection; false positive and negative identification; multiple stationary human targets; ultra-wideband radar