Indoor Multi-Target Tracking Exploiting Target Motion Characteristics and Prior Boundary Knowledge Using MIMO Radar

An indoor multi-target tracking method by exploiting target motion characteristics and prior boundary knowledge using multiple-input multiple-output (MIMO) radar is presented in this paper. The main task is to consistently and accurately track the people in the room. The challenge of indoor multi-target tracking is the mutual interference of target echo signals and the impact of multipath effects. In this paper, we first conduct long-short term preprocessing to remove static clutter, separate strength and weakness targets, and generate strength and weakness measurements. Meanwhile, we utilize prior boundary knowledge to eliminate multipath effects outside the boundary. Then, we manage trajectories based on the motion characteristics of targets and adopt different association and tracking strategies according to the trajectory types. Experimental results demonstrate that the proposed method achieves tracking errors of less than 0.1 m in various scenarios, with an average accuracy of 97.26% in people counting, which not only achieves high-precision target tracking but also outperforms existing methods in people counting performance.