基于动态贝叶斯网络的空袭目标威胁评估

针对现有方法在处理不确定性信息推理上的不足，提出一种威胁评估的动态贝叶斯网络模型。基于对动 态贝叶斯网络的研究及对空袭目标威胁影响因素的分析，给出网络中节点的状态转移概率表和条件概率表，结合证 据观测值推理得到目标威胁的后验概率，对典型航路空袭目标的威胁度进行仿真分析。结果表明：该模型合理有效， 能较准确地反映目标的真实威胁度，从而对空袭目标实施有效的末端拦截。

Threat Assessment of Air Attack Target Based on Dynamic Bayesian Network

In order to solve the shortcomings of the existing methods in dealing with uncertainty information reasoning, a dynamic Bayesian network model for threat assessment is proposed. The state transition probability table and conditional probability table of the nodes in the network are given based on analysis of dynamic Bayesian network and the analysis of the influencing factors of air strike target threat. The posterior probability of the target threat is obtained by reasoning with the evidence observations, and the threat level of the typical airway air attack target is simulated and analyzed. The results show that the model is reasonable and effective, and can accurately reflect the real threat level of the targets, thus effective terminal interception is implemented for air attack targets.