Research on Personnel Detection for Mine Accident Based on Channel State Information

doi:10.13190/j.jbupt.2018-223

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (4): 96-101.doi: 10.13190/j.jbupt.2018-223

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Research on Personnel Detection for Mine Accident Based on Channel State Information

SUN Chao-yu, GAO Shou-wan, YANG Xu, CHEN Peng-peng, NIU Qiang

School of Computer Science and Technology, China University of Mining and Technology, Jiangsu Xuzhou 221116, China

Received:2018-09-11 Online:2019-08-28 Published:2019-08-26

Abstract

Abstract: Aiming at the problems of high cost, short detection distance and high false alarm rate in traditional rescue methods, a new method for personnel detection based on channel state information is proposed. First, the state detection module determines the degree of the activity according to the Gaussian mixed distribution. Second, the breath detection module uses periodicity of the influence of human on channel state information to extract breathing, and to find the breathing frequency of the people who remain inactive. Finally, we evaluated the system in a variety of parameters. The experimental result verifies that the system has high accuracy and robustness,and the average recognition rate can reach 90%.

Key words: channel state information, Gaussian mixed distribution, foreground detection, personnel detection

CLC Number:

TP391

SUN Chao-yu, GAO Shou-wan, YANG Xu, CHEN Peng-peng, NIU Qiang. Research on Personnel Detection for Mine Accident Based on Channel State Information[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(4): 96-101.

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Research on Personnel Detection for Mine Accident Based on Channel State Information

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