BP Neural Network Based CSI Device-Free Target Classification Method

doi:10.13190/j.jbupt.2019-035

Journal of Beijing University of Posts and Telecommunications ›› 2020, Vol. 43 ›› Issue (1): 40-45.doi: 10.13190/j.jbupt.2019-035

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BP Neural Network Based CSI Device-Free Target Classification Method

JIANG Fang, ZHANG Nan-fei, HU Yan-jun, WANG Yi

Key Laboratory of Intelligent Computing and Signal Processing(Anhui University), Ministry of Education, Hefei 230601, China

Received:2019-03-03 Online:2020-02-28 Published:2020-03-27
Supported by:

Abstract

Abstract: Aim at the imbalance between accuracy and expense, the heavy workload of manually extracting features in current device-free target classification systems, a channel state information (CSI) device-free target classification method based on error back propagation (BP) neural network is proposed. By extracting the CSI of the WiFi signal as the base signal and combining the neural network method with the characteristic of autonomous learning data features, the BP neural network training model is designed, which reduces the overhead caused by the manual extraction feature. Taking the height classification as an example, an experiment is carried out, and it is shown that the proposed method can distinguish four different height segments, and the average classification accuracy can reach more than 90%.

Key words: channel state information, error back propagation neural network, device-free target classification

CLC Number:

TN929.53

JIANG Fang, ZHANG Nan-fei, HU Yan-jun, WANG Yi. BP Neural Network Based CSI Device-Free Target Classification Method[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(1): 40-45.

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BP Neural Network Based CSI Device-Free Target Classification Method

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