Phase-Calibration-Based 3-D Beamspace Matrix Pencil Algorithm for Indoor Passive Positioning and Tracking

In the context of integrated sensing and communication (ISAC), indoor device-free positioning and tracking technology based on channel state information (CSI) has become a key and significant branch. CSI extracted by high-bandwidth chips is not widely used for sensing due to problems of clock asynchrony and phase locking instability. This article implements passive positioning based on the CSI collected by the bcm4366 Wi-Fi chip. First, through extensive testing and observation, we describe the unstable phase difference phenomenon of the radio frequency (RF) channel of the bcm4366 chip. Calibrating phase ambiguity (PA) is implemented by a phase detection and compensation method. Based on this, a 3-D beamspace matrix pencil (BMP) algorithm is proposed to jointly estimate the angle of arrival (AoA), time of flight (ToF), and Doppler frequency shift (DFS) of CSI dynamic targets. Finally, passive localization is achieved based on joint multiparameters. Experiments verify that the 3-D BMP algorithm is superior to the existing algorithms in terms of tradeoff estimation accuracy and computational complexity. The positioning scheme based on 3-D BMP effectively reduces the positioning error after eliminating PA. In the single-link case, the median localization errors of the activity room and meeting room scenarios reach 0.42 and 0.55 m, respectively.

Automated summary

In this article, indoor device-free positioning and tracking technology based on channel state information (CSI) collected by the bcm4366 Wi-Fi chip is implemented. A phase detection and compensation method is used to calibrate phase ambiguity, and a 3-D beamspace matrix pencil (BMP) algorithm is proposed to estimate the angle of arrival (AoA), time of flight (ToF), and Doppler frequency shift (DFS) of dynamic targets. Passive localization is achieved based on joint multiparameters.