A Simplified JPDA Multi-target Tracking Algorithm for Dense Clutter Environment

To simplify the computational complexity of Joint Probabilistic Data Association (JPDA) and enhance the real-time performance of JPDA algorithm, a new simplified JPDA algorithm was proposed in this paper. Firstly, according to the association rules between the trajectory and the measurement of the target, a new method to calculate the simple association probability is defined. Then, the influence of the public measurement on the target is analyzed to modify the association probability. The algorithm does not need to split the confirmation matrix, and the problem of combinatorial explosion caused by the increase of echo density in the dense clutter environment can be effectively solved. The simulation results show that the simplified JPDA algorithm can greatly shorten the computation time and improve the real-time performance while keeping effective tracking of the target.