A hybrid fuzzy adaptive tracking algorithm for maneuvering targets

A new hybrid fuzzy adaptive algorithm for tracking maneuvering targets is proposed in this paper. The algorithm is implemented with fuzzy inference system (FIS) and current statistical model and adaptive filtering (CSNIAF). The CSNLAF algorithm is one of most effective methods for tracking the maneuvering targets. It has a higher precision in tracking the maneuvering targets with larger accelerations while it has a lower precision in tracking the maneuvering targets with smaller acceleration. In the proposed algorithm, to overcome the disadvantage of the CSNLAF algorithm, the covariance of process noise CSNLAF is adjusted adaptively by the output of a FIS. The input of the FIS is discrepancy of the covariance process noise from its actual value, where the actual value can be obtained based on filter innovation properties. Simulation results show that in spite of having simple structure for the proposed algorithm, it can also improve the precision of the CSNLAF algorithm in a wide range of target maneuvers significantly.