Probabilistic Track Initiation Algorithm Using Radar Velocity Information in Heavy Clutter Environments

In this paper, we propose a novel probabilistic track initiation algorithm using velocity information of measurements. The velocity information is converted to a probabilistic function and it is used to calculate the track score for track initiation. Moreover, we introduce the scheme of Non-Maximum Suppression (NMS) to determine candidate targets for tracking in terms of the track score. To verify the effectiveness of the proposed algorithm, we designed a simulator for target tracking. The simulation results show that the proposed algorithm has lower false track probability compared to conventional algorithms in heavy clutter environments.