Path re-planning decision-making model for UAV based on target state estimate

The application of varied discrete dynamic Bayesian network (VDDBN) in unexpected mobile threats is not available as it is used in the perceiving of pop-up still threats. Therefore, a new decision-making model of the re-planning for UAV is proposed. Under the situation without knowing the state of the mobile threat target, a target state estimate model is created based on dynamic Bayesian network (DBN) with the combination of Kalman filter theory, which is added on the path re-planning model as a module to make the re-planning decision. The simulation results show the correction of the decision-making model.