A novel data association algorithm based on intuitionistic fuzzy clustering

In this paper, a new data association algorithm based on intuitionistic fuzzy clustering for multi-target tracking in cluttered environment was proposed. In the proposed algorithm, the joint association probabilities in JPDAF are reconstructed by utilizing the intuitionistic fuzzy membership degree of the measurement belonging to the target. In order to compute the intuitionistic fuzzy membership degree, a new intuitionistic fuzzy clustering method is proposed. At the same time, to deal with the uncertainty of the measurements, a new weight assignment is introduced. Finally, the simulation results show that the proposed algorithm is effective, and the performance of tracking is higher than the JPDAF algorithm.