Application of dynamic Bayesian networks in tactical situation assessment
动态贝叶斯网络在战术态势估计中的应用*

A dynamic Bayesian networks model for situation assessment is constructed in this paper. The model considers discrete variable set as the object of study. Since the dynamic Bayesian networks model satisfy the Markovian property and stationary, the complexity of the networks is reduced. Compared with Bayesian networks , this dynamic Bayesian networks model takes temporal factor into account . Through this model, the current situation assessment is not only associated with the evidence at the moment ,but also with previous situation . Simultaneously, the next time situation can be predicted . The junction tree algorithm and Bayesian inferencing software is used in the experiments . Experimental results show that the situation assessment result is better than that of Bayesian networks and that the dynamic Bayesian networks model is effective.