Situation assessment of far-distance attack air combat based on Mixed Dynamic Bayesian Networks

Automatic and accurate far-distance air attack combat situation assessment is an essential problem for air combat situation assessment and decision-making support system. Through analyzing the process of far-distance attack air combat, a set of characteristic elements is acquired. Mix-state Dynamic Bayesian Networks situation assessment model is established by setting the characteristic elements as nodes and the calculation method of the attack probability is deduced to solve the inference problem of Mix-state Dynamic Bayesian Networks. The simulation results demonstrate that the model for far-distance attack air combat situation assessment is consistent with the actual situation.