INVESTIGATION ON DATA ASSOCIATION PROBLEM OF MULTI-MANEUVERING TARGET BY NEURAL NETWORK

The properties of the joint probabilistic data association (JPDA) in multi-maneuvering target tracking are analyzed in this paper, then reduced to be a sort of constraint combinatorial optimization problem. In the same way used in "traveling salesman problem" by neural network, the combinatorial explosion of computation quantity of JPDA can be solved. Simulations prove the effectiveness of the neural joint probabilistic data association (NJPDA) method. In dense multi-return environments the superiority of NJPDA has been showed more fully.