An algorithm of maneuvering target tracking based on interacting multiple models and fuzzy neural network

An algorithm which interacts current statistical model and constant speed model together can have no limit to the magnitude of target turn rate and its variety. The network which combines neural network with fuzzy logic inference not only has the ability of self-learning, association, and optimization structure in neural network, but also has the advantage of easy understanding of fuzzy inference. In this paper, fuzzy neural network is introduced into the interacting multiple model algorithms. It can adjust the structure of network itself according to input parameters. The Monte-Carlo simulation results show the method is valid.