An improved algorithm for maximum-likelihood based approach for a multitarget tracking problem

It has been shown that the optimal solution for the matching problem in multi-target tracking, when both estimated measuring bearing data and actual measuring data are known, can be found from among N different matchings. This paper shows by experiment that the costs of the N different possible solutions constitute a bimodal sequence, which suggests an algorithm of O(N-logN) complexity for the matching, lower than most known algorithms. An improved algorithm for the whole process of the multi-target tracking problem is obtained, and an improved performance is shown.