防空作战中异常空情威胁等级评估

摘要

Based on traditional model of threat assessment model, with consideration of various elements' impacts from both sides of friend and foe, this paper puts forward a new method in order to assess the threat level of everyday anomaly air situa-tion. This method uses the dynamic Bayesian network to analyze the attack intention of the target and its combat ability in or-der to deduce the air situation target information and consequently acquire the level of threat of the target which is regarded as the gain of anomaly air situation. Meanwhile, RBF fuzzy neural network is adopted to evaluate all of elements such as infor-mation acquisition, interception and strike and others that are related to our capabilities of air defense so as to access the lev-el of capability in dealing with emergencies in anomaly air situation. Finally, this method provides the threat level of anomaly air situation in the form of sum and difference. The simulation result has proved the scientificity and effectiveness of this method and the calculation results conform to the real situation.%为有效评日常估防空作战中异常空情的威胁等级,在传统威胁评估模型的基础上,综合考虑敌我双方多种因素的影响,提出了异常空情威胁等级评估的新方法.利用动态贝叶斯网络从目标攻击意图和作战能力角度出发对空情目标信息进行推理得到目标威胁程度,作为异常空情的收益;运用RBF模糊神经网络对影响我方防空作战能力的信息获取、拦截打击等因素进行评估得到我方异常空情应急处置能力水平,作为异常空情的成本,最后以和差的形式给出异常空情威胁等级.仿真结果表明该方法科学有效,计算结果符合处置实际.