动态贝叶斯网络在通信对抗目标选择中的应用

Application of Dynamic Bayesian Network in Target Selection of Communication Countermeasure

针对复杂战场环境下通信对抗干扰目标选择问题,设计了目标选择三级功能模型,重点从目标价值性、目标威胁性和干扰可行性3个方面分析了影响目标干扰优先等级判断的因素,利用离散动态贝叶斯网络构建了目标干扰优先级评估模型,并给出了评估模型的直接推理算法和目标选择的算法流程,最后,结合设计的案例对提出的目标选择方法进行了仿真验证。结果表明,在战场信息不完整的情况下,该模型可以综合考虑前后时刻的历史结果和实时信息,对干扰优先级进行有效的分析预测,较好地实现了通信对抗干扰目标的有效选择。

Considering the problem of target selection in communication countermeasure under complex battlefield environment, a three-level function model of target selection was designed. The factors that have effect on the target＇s jamming priority evaluation were analyzed from three aspects of target value, target threat degree and jamming feasibility. A model of jamming priority evaluation was constructed based on dynamic Bayesian network, and ratiocinated algorithm was proposed. The method of target selection was verified by simulation experiment. The simulation result showed that the model can combine historical information with real-time information synthetically and make analysis on jamming priority effectively with uncompleted battlefield information, thus can implement effective target selection in communication countermeasure.