Indoor target passive tracking method based on WiFi multi-dimensional parameter characteristics

Abstract

The invention provides an indoor target passive tracking method based on WiFi multi-dimensional parameter characteristics. The method comprises the following steps: firstly, eliminating a phase errorand a static path signal component contained in original channel state information (CSI) by adopting a conjugate multiplication method so as to obtain a dynamic path signal component; then, using a serial interference elimination method for carrying out signal arrival angle, flight time and Doppler frequency shift multi-dimensional parameter initialization, and then using a frequency domain spacealternating generalized expectation maximization algorithm based on noise updating for completing time-frequency-space multi-dimensional parameter joint estimation; secondly, selecting a target path signal from the plurality of path signals by using a mixed data association method based on a minimum-cost multi-path network; and finally, constructing an ellipse-straight line joint model by utilizing the target path signal parameters to realize target positioning and tracking. Compared with an existing passive tracking technology, the method is based on existing commercial WiFi equipment, extracustomized hardware is not needed, high-precision parameter estimation is achieved, and then target tracking is achieved.

Description

technical field [0001] The invention relates to the technical field of wireless positioning, in particular to an indoor target passive tracking method based on WiFi multi-dimensional parameter features. Background technique [0002] With the rapid development of the Internet of Things, human beings have gradually entered the era of intelligence. A large number of smart devices and systems have been developed and applied one after another, such as smart home systems, smart care systems, and smart building systems. As the key technology of the above applications, indoor tracking is getting more and more attention. Because active indoor target tracking requires users to carry additional equipment, which causes inconvenience to users and is not applicable in some specific environments, therefore, indoor passive target tracking technology has attracted the attention of many researchers. [0003] In recent years, a large number of passive target tracking technologies have been p...

AI Technical Summary

Problems solved by technology

Although the target tracking technology based on feature matching has high precision, it is easily affected by environmental factors. When the indoor environment changes, such as changing the position of furniture or adding new large-scale equipment in the environment, the fingerprint features at the same position will change, and offline Data collection requires a lot of manpower and material resources

The target tracking technology based on signal parameters uses fine-grained channel state information to estimate channel parameters such as signal angle of arrival, time of flight, and Doppler frequency shift, thereby avoiding heavy deployment and training, but this method is due to The direct path signal and noise make it difficult to extract the target reflection path signal, which seriously affects the parameter estimation accuracy

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