Based On Dynamic Bayesian Networks Of Battlefield Information Forecast And Evaluation

In information war, the battlefield situation assessment has become one of the central technologies in modern command decision. The situation assessment is essentially a reasoning process on decision level, which based on battlefield situation. The main problems of situation assessment include:(1) informations are uncertain because of the limiting of the reconnaissance;(2) the existing assessment ignores their own safety, which focuses enemy damage. So the assessment according the dynamic uncertain informations become the urgent problem.In view of the advantage of the dynamic bayesian network(DBN) in processing uncertain informations. In this paper forecasting and evaluating are based on DBN. The main task in this paper includes:(1) Forecasting and evaluating proves to be feasibility based on DBN. BN is the ideal model to solve the uncertain problems, and the DBN is better then the BN. The feasibility of DBN was proved by an example.(2) The DBN model of battlefield situation assessment. In this paper situation assessment was divided to target damage and own damage.(3) A correlated example based on DBN. The feasible and reasonable of the evaluation results are demonstrated by a correlated example.Through the analysis of a case that compared with the BN, the DBN are more exactly with the result of forecasting, and it also can provide decisions for the commander of the battlefield.