Passive tracking based on data association with information fusion of multi-feature and multi-target

Abstract

A new data association algorithm based on information fusion of multi-feature and multi-target in passive tracking is proposed in this paper. It uses more features of the target such as the frequency, PRI, while the traditional algorithms only use the features directly correlative with the target state such as DOA, TOA. Based on the information fusion of multiple features with DS evidence theory, the decision of synthetic data association of all the targets is made. With the help of computer simulations, it is proven that the proposed algorithm is superior to the NN method and the expanded NN method.