Title:
CSI METHOD FOR RECOGNIZING HUMAN FALL IN WI-FI INTERFERENCE ENVIRONMENT
Document Type and Number:
WIPO Patent Application WO/2021/160189
Kind Code:
A1
Abstract:
The present invention relates to a method for identifying a human fall by dynamic sub-carrier selection of a Wi-Fi CSI in a Wi-Fi interference environment, belonging to the technical field of wireless communications. In the method, CSI interference intensity and a CSI active ratio are first analyzed, a Wi-Fi interference feature mapping matrix is constructed, and the matrix is used to calculate an interference index of each channel to achieve interference discrimination. Then, by means of a dynamic subcarrier selection algorithm CSI-DSSA based on the interference index, the subcarrier combination having the weakest cross-correlation in the interference data is selected for interference processing, and a multi-link data fusion CSI-MLDF method is analyzed to aggregate the time-domain characteristic information of the multiple data streams in undisturbed data. Finally, the time-domain feature value is extracted and a SVM multi-activity classification model is constructed in a Wi-Fi interference environment to obtain a fall action recognition result. The present invention can effectively improve the recognition accuracy of human falling action in a Wi-Fi interference environment.
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Inventors:
XIE HAOFEI (CN)
LUO YUNXIAO (CN)
ZHOU YICHAO (CN)
GUO XIAOFENG (CN)
CHEN XINYUE (CN)
ZHANG YINJIE (CN)
WANG JIAXIN (CN)
LUO YUNXIAO (CN)
ZHOU YICHAO (CN)
GUO XIAOFENG (CN)
CHEN XINYUE (CN)
ZHANG YINJIE (CN)
WANG JIAXIN (CN)
Application Number:
PCT/CN2021/081494
Publication Date:
August 19, 2021
Filing Date:
March 18, 2021
Export Citation:
Assignee:
UNIV CHONGQING POSTS & TELECOM (CN)
International Classes:
G06K9/00; H04W4/33
Foreign References:
| CN111225354A | 2020-06-02 | |||
| CN110730473A | 2020-01-24 | |||
| CN110337066A | 2019-10-15 | |||
| CN109581303A | 2019-04-05 | |||
| US20180198548A1 | 2018-07-12 |
Other References:
OSHIGA OMOTAYO; SULEIMAN HUSSEIN U.; THOMAS SADIQ; NZEREM PETRUS; FAROUK LABARAN; ADESHINA STEVE: "Human Detection For Crowd Count Estimation Using CSI of WiFi Signals", 2019 15TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTER AND COMPUTATION (ICECCO), IEEE, 10 December 2019 (2019-12-10), pages 1 - 6, XP033744901, DOI: 10.1109/ICECCO48375.2019.9043195
Attorney, Agent or Firm:
TIDYTEND INTELLECTUAL PROPERTY LAW FIRM (CN)
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