基于改进G-GIFSS算法的雷达LPI性能评估方法

Radar LPI performance assessment method based on extended G-GIFSS algorithm

合理的雷达低截获(low probability of interception,LPI)性能评估方法是提高其隐身性能的基础。针对雷达LPI性能难以有效实时评估的问题,提出一种群广义直觉模糊软集(group-generalized intuitionistic fuzzy soft sets,G-GIFSS)算法与主客观权重相结合的雷达LPI性能评估方法。首先从反映雷达低截获性能的3个准则层信号层、功率层以及天线层确定6个目标属性指标层,选择直觉模糊集熵法确定客观权重、层次分析法((analytic hierarchy process,AHP))确定主观权重,并线性合成主客观权重。结合G-GIFSS算法利用多专家参量集的优势,对雷达LPI性能进行综合评判。通过案例分析并与经典评估方法对比,验证了该方法的优越性。

Rational radar low probability interception （LPI） performance assessment method is the basis of improving radar stealth performance. For it is difficult to assess radar LPI performance in time and effectively, an algorithm combining group-generalized intuitionistic fuzzy soft sets （G-GIFSS） with objective and subjective weight is proposed. Firstly, it chooses six index layers from three rule layers which reflect radar LPI performance. The intuitionistic fuzzy set entropy is used to get objective weight and the analytic hierarchy process （AHP） is used to get subjective weight. Then subjective and objective weights are combined linearly. With the advantage of several experts＇ parameter sets of the C-GIFSS algorithm, radar LPI performance is evaluated comprehensively. The case analysis and comparison with classical assessment algorithms show that the algorithm is more effective.