Target Tracking and Ghost Mitigation Based on Multi-view Through-the-wall Radar Imaging
Huquan Li, Guolong Cui, Shisheng Guo, Lingjiang Kong, Xiaobo Yang
Abstract
Multiple human target tracking in an enclosed structure is a critical mission for through-the-wall radar imaging (TWRI). Current efforts monitor the surveillance area from a particular view, where the ghost targets caused by the multipath and shadow effects would introduce numerous fake tracks. In this paper, we deal with the problem of target tracking exploiting multi-view TWRI. A sequential filtering framework is utilized to estimate the tracks of both the human and ghost targets based on the measurements from multiple radar nodes. Subsequently, a ghost mitigation method is proposed based on the view-dependent features of the ghosts. Finally, the proposed algorithm is validated by numerical simulations.