Data Association for Infrared Search and Track System

Data association is one of the key techniques on bearing-only tracking with infrared search and track (IRST) system. A new data association algorithm based on information fusion is proposed in this paper. Firstly, by considering the special feature of IRST system, the new method constructs several kinds of evidences that are based on the multi-type information, such as angular measurement, intensity level and so on. And then all results from different aspects are fused by utilizing Dempster combination rule. Finally, the association decision is obtained by maximizing the final mass function. The simulation results show that the proposed approach has better performance than the traditional ones. As observation conditions deteriorate, the advantage of new method becomes obvious. For uncertain data, this new data association algorithm based on evidence theory is excellent by utilizing reasonably the measurements