Data association algorithm of infrared search and track system

For a single observation of infrared search and track (IRST) system, a new data association algorithm of passive tracking is proposed. Firstly, according to the measurements of infrared sensor, several kinds of evidences arc constructed from different views. Then the information of multiple features are fused by using D-S combining rule. Finally, the association results are obtained by maximizing the basic probability assignment function (BPAF). By utilizing different information of the measurements reasonably, the new data association algorithm based on D-S evidence theory overcomes the problem of uncertain data in the traditional methods. The simulation results show that the proposed approach has better performance in data association.