Abstract:

After a thorough study on the Mbest hypothesis method for track association and hypothesis management, this paper proposes a novel hypothesis management technique based on establishing the combinable association sets, and a novel track association algorithm is brought forth by utilizing the technique. This approach can reduce the number of hypothesis efficaciously and provide accurate track association and  shorten the run time. It is appropriate to multitarget track association under dense clutters. The simulation results testify the validity of the present approach.

Key words: M-best hypothesis；hypothesis management；K-similar rule；track association algorithm