Damage assessment of formation air-to-ground attack based on Bayesian networks

Battle damage assessment system is important in modern combat along with high-tech of weapon, complexity of battlefield and quicken of combat rhythm. Aim at the diversity, uncertainty and illegibility of battle damage assessment data sources, based on the merit of Bayesian networks have advantages on deal with uncertainty inference, the Bayesian networks models of air-to-ground battle damage assessment has been built. The Bayesian inference algorithm has been given out. The simulation example of air-to-ground combat damage assessment also has been delt with Bayesian networks. The simulation results showed that the damage assessment models could improve the assessment accuracy and the algorithm is simple, perspicuity and apt realization.