Computer Science ›› 2019, Vol. 46 ›› Issue (12): 266-271.doi: 10.11896/jsjkx.190200349

• Graphics ,Image & Pattern Recognition • Previous Articles     Next Articles

Non-cooperative Human Behavior Recognition Method Based on CSI

LI Xiao-wei, YU Jiang, CHANG Jun, YANG Jin-peng, RAN Ya-xin   

  1. (School of Information Science and Engineering,Yunnan University,Kunming 650500,China)
  • Received:2019-02-23 Online:2019-12-15 Published:2019-12-17

Abstract: Currently,Wi-Fi-based wireless personnel perception technology is widely used in anti-intrusion security monitoring,human health care,gait recognition and other fields,regarding this,this paper proposed a non-cooperative human behavior recognition method.The channel state information (CSI) of Wi-Fi signals can be used to recognize five dynamic activities:walking,sitting-standing up,squatting,jumping and falling.The method uses a SIMO system to collect CSI data,and after performing pre-processing on the CSI amplitude and phase respectively,implements a three-step computational cost reduction mechanism:subcarrier fusion,rejection of bad data link based on mobile variance threshold,and data segmentation of dynamic time window based on wavelet transform.Then activity features are extracted and extended from the time domain to the frequency domain.By analyzing the characteristics of the Doppler power spectrum,the utilization of the CSI signal is improved.Experiment results show that the overall recognition rate increases with the use of feature dimensions.Optimized by two rounds of voting,the combined classifier weighted voting method is increasing the overall recognition rate of five dynamic activities to 90.3%.And compared to RSSI,the advantages of CSI in the field of human behavior recognition are more prominent.

Key words: CSI, Non-cooperative, Wavelet analysis, Dopplerpower spectrum

CLC Number: 

  • TP391.4
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