Application of Dynamic Bayesian Network in Battlefield Situation Assessment
Peng Zhang · Electronics Optics & Control · 2010
The Bayesian Network ( BN) is not able to predict the future when it is used for situation assessment since the system parameters can not be updated in real-time. To solve this problem,we studied the application of Dynamic Bayesian Network (DBN) in battlefield situation assessment. The factor of time was introduced to construct the network model. The probability parameters and inference procedure were analyzed,and Kalman filter algorithm was used in simulation of the inference. The simulation result proved the feasibility of the dynamic inference model. Since information of time from reconnaissance data can be used effectively in DBN for dynamically processing the factors that have effect on analysis and decisionmaking,thus it is of great significance for decision-making of commanders.