A HRRP feature-aided multi-target JPDA algorithm

For solving the problem that traditional Joint Probabilistic Data Association (JPDA) algorithm with high complexity can’t meet the real time performance of data association in complicated electromagnetic environment, a JPDA algorithm based on feature aided of high resolution one-dimensional range profile (HRRP) is proposed in this paper. Firstly, the similarity of HRRP feature is calculated between the measurement and the target. Then, the number of the feasible event is reduced with the HRRP feature similarity aided JPDA algorithm to complete the gate search. Finally, the probability of the feasible event is modified by using the HRRP feature similarity, and then modify the association probability of the measurement and the target. Simulation results show that this algorithm improves the correlation performance, and also greatly improves the real time performance of the algorithm.