自主飞行器在高度不确定环境下执行复杂作战任务,必须同时兼顾任务完成、战略生存和飞行安全进行自主决策。行为能力等级定量反应了平台健康状态和生存、作战能力,是自主决策的前提和依据,战场威胁级别则反应了外部环境的影响。给出了扩展态势评估的定义,研究了基于贝叶斯网络与模糊逻辑的评估算法,建立了评估模型,构建了自主决策算法,依据扩展态势评估结果进行自主决策,仿真并分析了评估和决策结果,表明方法的有效性。
Autonomous Flight Vehicle performs complex combat missions under significant uncertainties, which requires autonomous decision-making with consideration of mission success, strategic survival and flight safety. Performance capacity level (PCL) reveals the vehicle health state and combat capacity, which is the precondition and foundation of autonomous decision-making. Threat Level reveals the effect from external environments. The detail definitions of extended situation assessment were given and the Bayesian Belief Network and Fuzzy Logic based algorithms were discussed. The PCL assessment model was developed to give the on-line result. An autonomous decision-making algorithm based on expert system was proposed to generate the proper decision according to the assessment results. The simulation results of PCL assessment and the corresponding decisions were analyzed to illustrate the reasonability and effectiveness of the algorithms.