Indoor target passive tracking method based on WiFi Doppler frequency shift

Abstract

The invention provides an indoor target passive tracking method based on WiFi Doppler frequency shift. The method comprises steps of first, calculating a discrete coefficient by using channel state information (CSI) amplitude of a WiFi signal subcarrier, then using the discrete coefficient as a detection parameter, and realizing detection of a passive target by using hypothesis testing; then performing Fourier transformation on the CSI for a short time, so as to obtain a spatial spectrum of a signal, extracting a Doppler frequency shift value and a corresponding power value, and using a time sequence corresponding to the power value as a target moving direction marker discriminant feature; then designing a reference sequence according to a logarithmic decay model, performing sequence matching by using dynamic time warping (DTW), and identifying a moving trend of the passive target; and finally, estimating a moving speed of the passive target according to a geometric relationship between the Doppler frequency shift and target moving, so as to realize target tracking. Compared with the existing passive tracking technology, the method omits offline data collection and training, and has advantages of low cost and easy deployment.

Description

technical field [0001] The invention relates to the technical field of wireless tracking, in particular to an indoor target passive tracking method based on WiFi Doppler frequency shift. Background technique [0002] With the upgrading of consumption patterns and the vigorous development of the mobile Internet, more and more consumer electronics products have been tagged with intelligence and have gradually entered consumers' daily life, such as smart home, security monitoring, virtual reality, augmented reality etc. Trajectory tracking, as a key technology for these applications, has become a research hotspot. [0003] Vision-based tracking technology can achieve high tracking accuracy, but it relies on high-resolution images or videos, and can only work in visible environments and environments with sufficient light. The accuracy is seriously reduced in the environment. In addition, this technology also involves user privacy and high cost. In recent years, with the develo...

AI Technical Summary

Problems solved by technology

In the current passive tracking technology, some methods need to use specific equipment such as radar or custom hardware equipment for signal transmission and reception, the equipment is expensive and not universal; some algorithms need to collect data in the offline stage and perform feature model training , and then collect data online for matching. These methods are easily affected by the environment, that is, when the indoor environment changes, such as changing the position of items or adding larger items to the environment, it is necessary to re-collect data for training

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