A neural network based data association technique for tracking

A neural network based data association technique employing a Hopfield network to track multitargets is presented in this paper. The energy function of the Hopfield network with necessary constraints is derived by examining the travelling salesman problem (TSP). The data association probabilities are computed and applied to a Kalman filter tracker for each target. The performance of the proposed algorithm is compared to the conventional techniques. Simulation results reveal that the proposed neural network algorithm yields satisfactory performance.