Study on air combat tactics decision-making based on bayesian networks

Air combat tactics decision-making is a procession which full of complexity and uncertainty. The decision-making is uncertainty fusion reasoning with multi-sensors system. Aim to deal with the uncertainty in a dynamic decision-making process of air combat, bayesian network model of air combat tactics decision-making has been brought out based on the merits of bayesian networks on uncertainty reasoning. Firstly, the air combat tactics of beyond visual range (BVR) was analyzed in detail as a typical air combat example based on the combat situation of both sides. Secondly, the decision-making variables and reasoning rules were selected based on the tactics control mathematics model. Lastly, according to the decision-making variables and the reasoning rules, the bayesian networks model of BVR combat tactics decision-making was given out. Then the optimal tactics decision-making can be selected applied with the bayesian network inference algorithm. The method has been tested with given conditions. The simulation results have showed that the tactics decision-making models could improve the decision-making accuracy and intelligent and the algorithm is simple, perspicuity and apt realization.