A Novel Recognition Method of Aerial Targets Based on Improved D-S Evidence Theory and Fuzzy Theory

In air combat, the identification of aerial targets serv- es as the foundation and prerequisite for situation assessment and threat estimation. Aiming at the problem of air target recognition, a data fusion recognition method based on improved Dempster-Shafer (D-S) Evidence Theory and fuzzy theory is proposed in this paper. For the target information obtained by radar and other multi-source sensor devices, the members- hip function is constructed by fuzzy set theory, and converted into the Basic Probability Assignment (BPA) function of the target to be identified. Then D-S Evidence Theory is used for conflict evidence synthesis and fusion, and the Pignistic probability decision algorithm is employed for discriminant analysis ultimately, so as to realize the identification of air targets. Simulation results show that the proposed method is correct and effective, and improves the accuracy of target recognition to some extent.