Information Fusion Based On Dynamic Bayesian Network In The Threat Assessment Of The Battlefield

Battlefield threat assessment is a relatively new direction in the field of information fusion. In the battlefield environment, it has numerous information sources and most of them are uncertainty, Therefore, according to uncertain information, effective reasoning methods in the field of information fusion for battlefield threat assessment research becoming hot.This paper is mainly on the application of Dynamic Bayesian network in the threat assessment. Bayesian network is considered the strongest foundation for the mathematical theory of dealing with uncertainty. Dynamic Bayesian Network (DBN) is the development of Bayesian Network (BN). It has a good time evolution of the denotation capacity for the random variables. Bayesian network has the characteristic that it can combine priori knowledge and experience with the later data, and make them seamless integrated. Make use of closed-loop dynamic Bayesian network topology for continuous learning. It can reduce the uncertainty of Information integration. By the experiment of threat assessment simulations of the Unmanned combat aircraft. Proof the validity of the DBN using in threat assessment.Once this method been applied to practice, they will certainly be able to improve their operational decision-making process automation and intelligent.