Data association algorithm based on improved fuzzy C-means for multi-target tracking

A new data association algorithm based on improved fuzzy c-means (IFMC) for multi-target tracking in a cluttered environment was proposed. Firstly, the proposed algorithm was used to cluster the received measurements and then by introducing the conception of the fuzzy membership degree, the partition matrix of measurements to track is constructed. The proposed approach has a lower computational complexity in the expense of a little lower performance compared to the JPDA algorithm. Simulation results show that the arithmetic is an effective solution with less calculation to precision of association between measurements and measurements for multiple targets in a cluttered environment.