空空导弹在海背景下打击巡航导弹时,为避免鱼鳞光干扰,需要约束弹目交汇的视线方向。针对该场景,为了优选制导律,提出一种评估体系。将模糊层次分析法(FAHP)和熵权法相结合,得到结合主观和客观的评价权重,建立逼近理想解排序法(TOPSIS)评估模型,为优化计算结果,引入灰色关联度克服传统欧氏距离的缺陷。应用FAHP-熵权-TOPSIS模型对不同制导律在信息有偏差的情况下进行评估,通过对空空导弹脱靶量、视线角误差、攻击时间以及最大过载持续时间4项评价指标及其均值和均方差进行评估分析,应用蒙特卡洛方法对比分析联合偏置比例制导律、滑模制导律以及RBF神经网络滑模制导律三种制导律的性能。仿真实验证明,FAHP-熵权-TOPSIS综合评价方法可应用于制导律性能的评估。

When an air-to-air missile strikes a cruise missile against a sea background, it is necessary to constrain the direction of the line of sight where the missile and the target meet in order to avoid the interference of fish scale light. For this scenario, an evaluation system is proposed in order to prefer the guidance law. The fuzzy analysis hierarchy method (FAHP) and entropy weight method are combined to obtain the evaluation weights combining subjective and objective, the evaluation model of technique for order of preference by similarity to ideal solution (TOPSIS) is established, and the grey correlation is introduced to overcome the defects of the traditional Euclidean distance in order to optimize the calculation results. The FAHP-entropy weight-TOPSIS model is applied to evaluate different guidance laws in the case of information bias, and the four evaluation indexes of air-to-air missile miss distance, line-of-sight error, attack time and maximum overload duration, as well as the mean and mean squared deviation of the four indexes are evaluated and analysed, and the Monte Carlo simulation is applied to compare the three types of guidance laws of the joint bias-proportional guidance law, the sliding-mode guidance law, and RBF neural network sliding mode guidance law to compare the performance of the three guidance laws. The simulation experiment proves that the comprehensive evaluation method of FAHP-entropy weight-TOPSIS can be applied to the evaluation and preference of the performance of the guidance law.