Neuro-fuzzy techniques for airborne target tracking

In air defense system, surveillance radar with conventional tracking algorithm may not be able to track multiple targets accurately especially in a dense and cluttered environment, jamming and electronic counter measures. In this paper, an investigation has been carried out to implement the conventional tracking algorithms in conjunction with the Neuro-Fuzzy technique in such a way that the tracking error can be minimised and the maneuvering target trajectories can be predicted. The tracking performance of the proposed approaches, called Neuro-Fuzzy aided Joint Probabilistic Data Association (NFJPDA) and Neuro-Fuzzy aided Nearest Neighbour Probabilistic Data Association (NFNNPDA), have been simulated Results show that the proposed approaches yield improvement in tracking accuracy as well as resolving closely spaced tracks.