Maneuvering multi-target tracking based on PHD filter for phased array radar

Tracking an unknown and time-varying number of maneuvering targets is a challenging problem in the presence of noise, clutter, uncertainties in target maneuvers, data association, and detection. To solve this problem, a novel multiple maneuvering targets tracking algorithm called multiple models unbiased converted measurement probability hypothesis density (MM-UBCM-PHD) is proposed in this paper for phased array radar. The method not only solves the converted error in the direction cosine coordinate, but also avoids higher bias estimation of target number. The simulation results indicate that the proposed method has better performance in terms of state filtering and target number estimation.