Engagement maneuvering strategy of air combat based on fuzzy markov game theory

Abstract

Based on the framework of markov game theory, the attack engagement maneuvering strategy of 1 vs. 1 air combat is studied. First, the markov game model of air combat of two fighters is established with an introduction of its state space description and action set, and the maneuvering target set of both rivals is established. Second, the fuzzy theory is utilized and a fuzzy Markov model framework is introduced with its fuzzy state space and fuzzy reward function. Then, with the fuzzy markov game, the Nash-Q learning method is adopted to obtain the optimized strategy of the fighters. At last, a simulation shows that with the method in this paper, the 1 vs. 1 air combat decision making can be solved and the method is effective.