Two Improved m-best Multiple Hypothesis Tracking Algorithms
Yingjie Shi · Fire Control and Command Control · 2011
In Multiple Hypothesis Tracking(MHT) algorithm,one challenge is the number of feasible hypothesis matrices increase rapidly with the number of targets and measurements.To handle with this problem,two improved m-best MHT algorithms are proposed by reducing the dimension of the row vectors and column vectors of the cluster matrix.The simulation is carried out based on a multiple targets tracking scenario,and the results show that the methods significantly reduce the amount of calculation by avoiding split of high-dimension cluster matrix. Moreover,the methods simultaneously implement the measurement-track association of multiple targets,extending application scope.