Cooperative Multi-Target Tracking Based on Multi-Detection TPHD in MIMO-OFDM Systems
Chen Zhong, Lan Tang, Ying-Chang Liang
Abstract
This paper presents a passive multiple trajectories tracking system with multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) signals transmitted by the base station (BS). Firstly, we propose a Bayesian learning method to obtain the coarse estimations of targets and clutter, which are utilized for trajectories tracking. Considering the potential for a target to generate multiple measurements in overlapping areas of sweeping beams and non-Poisson clutter, we extend the trajectory probability hypothesis density (TPHD) filter to multi-detection TPHD (MD-TPHD) filter with non-Poisson clutter and provide its Gaussian mixture implementation. Simulation results show the performance of the algorithm.
BibTeX
@inproceedings{icassp2025_cooperativemulti,
title = {Cooperative Multi-Target Tracking Based on Multi-Detection TPHD in MIMO-OFDM Systems},
author = {Chen Zhong and Lan Tang and Ying-Chang Liang},
booktitle = {ICASSP 2025},
year = {2025}
}