Extend Kalman Gaussian mixture probability hypothesis density filter based on radar and IR sensor fusion

In this paper, we proposed a method to fuse data from radar and IR sensor in Extend Kalman probability hypothesis density (EK-GMPHD) filter. Firstly the multi-target is estimated with infrared (IR) sensor using EK-GMPHD filter, and then the filtering results are fused with measurements from radar through sequential filter, in this way, the multi-target state is updated at the tracking system. Under false alarms, missed detections and dense targets environment, this method has a high reliability when tracking multi-target. Simulation experiments are presented to demonstrate the performance of the proposed method.