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将动态贝叶斯网络应用于机载雷达侦察效能评估中,从而实现了一段时间内机载雷达侦察效能的动态评估。选取随战场环境、操作员水平等变化的因素作为影响机载雷达侦察效能评估的指标,并采用模糊分类方法形成各指标的状态集合;构建基于Netica的动态贝叶斯网络模型,运用德尔菲法确定模型参数及隶属度函数,利用贝叶斯网络的推理模型以及相应的推理算法,对机载雷达侦察效能进行动态评估。仿真结果表明:该方法能够科学、有效地评估机载雷达侦察效能。
The dynamic Bayesian network is applied to the airborne radar reconnaissance effectiveness evaluation, so as to realize the dynamic assessment of airborne radar reconnaissance performance over a period of time. The factors affecting the airborne radar reconnaissance effectiveness evaluation are selected as the factors influencing the battlefield environment and the operator’s level, and the state sets of each index are formed by using the fuzzy classification method. A dynamic Bayesian network model based on Netica is constructed. By using the Delphi method, Determine the model parameters and membership functions, the use of Bayesian network reasoning model and the corresponding reasoning algorithm, the airborne radar reconnaissance effectiveness of dynamic assessment. The simulation results show that this method can scientifically and effectively evaluate the airborne radar reconnaissance efficiency.