Abstract:

Aiming at the characteristic that a threat assessment of aerial targets requires to have the ability of an uncertain inference, as well as consider the influence of both discrete variables and continuous variables comprehensively, a Bayesian network model for a threat assessment of aerial targets is constructed. The learning method of continuous parameters with subjective knowledge and historical data is proposed to promote the accuracy for describing the dependency relationship among variables. The clique tree algorithm is used to make an inference of the threat assessment model of aerial targets. Simulation results verify the validity of the proposed method.