Skip to Main Content
In this paper, we present a multi-sensors data fusion method for target tracking. This approach uses local estimates of the object positions, then the estimates are sent to a central node, where the fusion is done. To achieve a globally optimized performance, these estimates are obtained by the neural network filters using a constant velocity motion model of the target. The coefficients of the filter are estimated by a neural network, then the estimated positions of the target are obtained. Simulation results in three sensors data tracking fusion system are given to show the effectiveness of the proposed algorithm.
Date of Conference: 0-0 0