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Action sequence detection-based user identity identification method applied to indoor WiFi environment

A technology of user identification and action sequence, which is applied in the field of user identification based on action sequence detection, can solve problems such as poor accuracy, and achieve the effect of improving data quality, reducing impact, and high-accuracy identification

Active Publication Date: 2017-12-29
NORTHWESTERN POLYTECHNICAL UNIV
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AI Technical Summary

Problems solved by technology

[0003] In order to overcome the deficiencies of the poor accuracy of the existing WiFi signal-based user identity recognition method, the present invention provides a user identity recognition method based on action sequence detection in an indoor WiFi environment

Method used

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  • Action sequence detection-based user identity identification method applied to indoor WiFi environment
  • Action sequence detection-based user identity identification method applied to indoor WiFi environment
  • Action sequence detection-based user identity identification method applied to indoor WiFi environment

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Embodiment Construction

[0019] refer to figure 1 . The specific steps of the user identity recognition method based on action sequence detection under the indoor WiFi environment of the present invention are as follows:

[0020] Step 1. In an indoor environment, using a laptop computer and a WiFi device, let the volunteer A participating in the experiment repeatedly squat, stand up, sit down, and stand up on a fixed position near the experimental equipment, and collect volunteer A channel state information data, and record the collected data. Similarly, the data of volunteers B, C, and D are collected.

[0021] Step 2, data preprocessing, select the Butterworth filter for denoising processing, and remove the noise existing in the data. According to the change frequency f of the CSI sequence caused by the human body movement is about 10-40 Hz and the sampling frequency Fs is 100 Hz, the cutoff frequency wc of the Butterworth filter is obtained.

[0022]

[0023] Step 3. Extract the action wavef...

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Abstract

The present invention discloses an action sequence detection-based user identity identification method applied to an indoor WiFi environment. The invention aims to solve the technical problem of low accuracy of an existing user identity identification method based on WiFi signals. According to the technical schemes of the method, sensing is realize through using devices such as commercial WiFi and notebooks; sensed data are preprocessed, so that the quality of the data can be improved; features are extracted from the data so as to depict user identities; a classification model is constructed; and the classification model is invoked to calculate the probability distribution of user identities of single actions; the probability distribution results of all identifiable actions in action sequences are put into statistics, so that identity identification is realized; and in the process of the identity identification, the data are used to accurately depict waveforms, and the user identities are judged many times through the action sequences, and therefore, the influence of complex environments on identification accuracy can be decreased, and high-accuracy identity identification is realized based on the results of a plurality of times of judgment.

Description

technical field [0001] The invention relates to a user identity recognition method based on WiFi signals, in particular to a user identity recognition method based on action sequence detection in an indoor WiFi environment. Background technique [0002] The document "Patent Application No. 201610841511.5 Chinese Invention Patent" discloses a user identification method based on WiFi signals, including WiFi transmitters, signal receivers and terminal equipment. This method takes advantage of the influence of the user on the channel state information when passing through the WiFi device. After denoising the channel state information, the shape features of the line-of-sight waveform are extracted, and the approximate coefficients of the line-of-sight waveform are calculated by discrete wavelet transform. Classify the shape features of the line-of-sight waveform for user identification. The method described in the literature uses waveform matching to realize user identification....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/04G06F2218/10G06F2218/12G06F18/24
Inventor 於志文夏卓越王柱辛通郭斌
Owner NORTHWESTERN POLYTECHNICAL UNIV
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