User-Centric Multi-Static Sensing for Joint User and Target Tracking in Mobile Wireless Systems

This paper presents a novel user-centric sensing framework, where a user equipment (UE) acts as the receiver of a multi-static radar sensing system and utilizes the communication signals emitted by base stations (BSs) and scattered by the targets for joint UE and target tracking. Specifically, we propose to locate the UE using the least squares (LS) estimator with a one-dimensional (1D) search and then develop a two-dimensional (2D) target identification approach using the estimated target location and motion of each path based on mean-shift clustering. After the motion parameters of the UE and targets are estimated, a joint UE and target tracking algorithm is designed based on the analysis of the localization and motion estimation errors. Extensive simulations corroborate the ability of our approach to estimate target parameters and cluster and identify targets. Specifically, the average estimation error of the target number is only 0.18. The speed and heading accuracy of the UE and targets is [0.121 m/s, 3.879°] and [0.199 m/s, 4.669°], respectively. In joint UE and target tracking, our scheme outperforms the benchmarks of the extended Kalman filter (EKF) and belief propagation (BP) by at least 33.16% and 10.29%, respectively, even though the EKF and BP require a-priori knowledge of the motion parameters and target identification.