Paper Info
Title
Csi Frequency Domain Fingerprint-Based Passive Indoor Human Detection
Abstract
Passive indoor personnel detection technology is now a hot topic. Existing methods have been greatly influenced by environmental changes, and there are problems with the accuracy and robustness of detection. Passive personnel detection based on Wi-Fi not only solves the above problems, but also has the advantages of being low cost and easy to implement, and can be better applied to elderly care and safety monitoring. In this paper, we propose a passive indoor personnel detection method based on Wi-Fi, which we call FDF-PIHD (Frequency Domain Fingerprint-based Passive Indoor Human Detection). Through this method, fine-grained physical layer Channel State Information (CSI) can be extracted to generate feature fingerprints so as to help determine the state in the scene by matching online fingerprints with offline fingerprints. In order to improve accuracy, we combine the detection results of three receiving antennas to obtain the final test result. The experimental results show that the detection rates of our proposed scheme all reach above 90%, no matter whether the scene is human-free, stationary or a moving human presence. In addition, it can not only detect whether there is a target indoors, but also determine the current state of the target.
Year
DOI
Venue
2018
10.3390/info9040095
INFORMATION
Keywords
Field
DocType
Wi-Fi, channel state information, device-free
Frequency domain,Data mining,Computer science,Real-time computing,Robustness (computer science),Fingerprint,Physical layer,Safety monitoring,Channel state information
Journal
Volume
Issue
ISSN
9
4
2078-2489
Citations 
PageRank 
References 
2
0.36
5
Authors
5
Name
Order
Citations
PageRank
Chong Han131432.63
Qingqing Tan220.36
Lijuan Sun311820.41
Hai Zhu48722.69
Jian Guo522127.43