Abstract: Track correlation is the main problem in the distributed multisensor system. This paper presents a generalized classical assignment algorithm based on the sequential track correlation criteria. This algorithm is actually a minimum problem under the restrict conditions, it belongs to the combined optimization problem and its computing burden increases heavily with the number of targets. Then the problem is dealt with by using the Hopfield neural network based on its ability of solving this kind of problem. Finally the simulation results are given, and the simulation experimental results illustrate that the generalized classical assignment algorithm can effectively solve the problem of track correlation, and that the neural network can decrease the computing burden and has higher correct association rate.

Key words: generalized classical assignment, track correlation, multisensor, neural network, information fusion