An improved fuzzy track association algorithm based on weight function

The technology of target data association is the premise and foundation of target tracking and information fusion, for the association quality will directly affect the accuracy and rationality of the subsequent information processing. In the fuzzy synthetic method, the Euclidean distance of target position and velocity are used as the fuzzy factor set, and the membership degrees are calculated through the fuzzy weight set to get the association result. This algorithm is effective when the targets are relatively sparse. But if the targets are rather dense, the position information usually leads to the false result, so the accuracy of the traditional algorithm is decreased. In this paper, a new improved algorithm based on the weight function is proposed. Taking the target position information into the weight function to update the fuzzy weight set dynamically, the improved algorithm in dense targets situation can get better result. Simulation results show the effectiveness of the proposed method.