普运伟,吴海潇,刘涛涛,等. 基于IVIF-VIKOR的雷达辐射源信号分选识别特征性能综合评价方法[J]. 电波科学学报,2022,37(1):15-22 + 78. DOI: 10.12265/j.cjors.2020196
      引用本文: 普运伟,吴海潇,刘涛涛,等. 基于IVIF-VIKOR的雷达辐射源信号分选识别特征性能综合评价方法[J]. 电波科学学报,2022,37(1):15-22 + 78. DOI: 10.12265/j.cjors.2020196
      PU Y W, WU H X, LIU T T, et al. Comprehensive evaluation method of radar emitter signal sorting and recognition features performancebased on IVIF-VIKOR[J]. Chinese journal of radio science,2022,37(1):15-22 + 78. (in Chinese). DOI: 10.12265/j.cjors.2020196
      Citation: PU Y W, WU H X, LIU T T, et al. Comprehensive evaluation method of radar emitter signal sorting and recognition features performancebased on IVIF-VIKOR[J]. Chinese journal of radio science,2022,37(1):15-22 + 78. (in Chinese). DOI: 10.12265/j.cjors.2020196

      基于IVIF-VIKOR的雷达辐射源信号分选识别特征性能综合评价方法

      Comprehensive evaluation method of radar emitter signal sorting and recognition features performancebased on IVIF-VIKOR

      • 摘要: 为解决雷达辐射源信号分选识别特征评价不够客观和缺乏评价依据等问题,提出了一种基于区间模糊原理、模糊交叉熵和多准则折衷法的特征评价方法. 首先通过区间模糊原理建立信噪比分级评价模型,并基于汉明距离进行寻优得出信噪比权重;其次结合信噪比权重和区间直觉模糊加权平均算子将分级模型整合成群决策矩阵,使用熵最大化法计算属性权重;最后基于多准则折衷法框架,采取模糊交叉熵实现特征方案排序. 仿真实验结果表明,所提方法能够给出与实际仿真实验相一致的分选识别特征评价排序结果,并优于逼近理想点方法,验证了所提方法的可行性和有效性.

         

        Abstract: In order to solve the problems of insufficient objective evaluation and lack of evaluation basis for the classification and identification of radar emitter signals, a group evaluation method based on interval fuzzy principle, fuzzy cross entropy and multi-criteria compromise method is proposed. Firstly, the signal-noise ratio (SNR) classification evaluation model is established by the interval fuzzy principle, and the SNR weight is obtained by optimization based on the Hamming distance. Secondly, the hierarchical model is integrated with the group decision matrix by combining SNR weight and interval intuitionistic fuzzy weighted average operator, and the attribute weight is calculated by the entropy maximizing method. Finally, based on the framework of multi-criterion compromise method, the fuzzy cross entropy is adopted to realize feature scheme sequencing. The simulation results show that the proposed method is able to give the sorting identification feature evaluation ranking results consistent with the actual simulation experiment, and is better than the ideal point approach method, which verifies the feasibility and effectiveness of the proposed method.

         

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