作战无人机(UCAV)**悬挂及使用方案对无人机作战效能有重要影响。从分析影响**备选方案的任务条件和目标威胁等级入手, 建立了UCAV外挂**使用方案优选模型。基于该模型提出了一种UCAV外挂**使用方案模糊神经网络智能优选算法。算法利用模糊神经网络良好的自适应和自学习能力,通过样本数据训练确定了模型因素间非线性复杂关系。最后, 运用该模型得到某型无人机编队的**方案使用优选结果, 并将仿真结果与实战**使用方案进行对比, 结果显示了该模型相同的优选能力, 为UCAV**使用开创了新的思路。

The weapon storage and application schemes of the Unmanned Combat Aerial Vehicles (UCAV)are very important for its combat efficiency.The factors that have effect on the weapon application such as threat levels and combat environment were analyzed and the optimization model of UCAV weapons'application schemes was built up.Based on this model a fuzzy neural network optimization algorithm for weapons'application schemes was adopted.By utilizing the good self-adaptability and self-learning capability of fuzzy neural network the nonlinear complex relationship between the factors of the model was determined through sample training.The optimized weapon selection scheme was obtained for a UCAV formation by using this model.Compared with the practical fighter weapons' application schemes simulation showed that the model has the same optimization ability which gives a new thought for research of weapon application of UCAVs.