雷达辐射源信号分选识别特征性能评价的改进灰色关联模型

Improved Grey Correlation Model for Performance Evaluation of Radar Emitter Signal Sorting and Recognition Features

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,构建了一种结合区间直觉模糊思想的改进灰色关联的特征评价模型。该模型引入信噪比维度来考察不同层次数据的动态差异,以区间型数据描述特征信息,建立区间直觉模糊综合决策矩阵;其次,采用特征间总离差最大化的优化模型来确定各指标权重;最后基于改进灰色关联框架,结合逼近理想点方法实现特征方案排序。仿真实验结果表明,所提方法能够给出与实际情况相一致的分选识别特征评价排序结果,并和未改进的灰色关联法分析结果基本一致,验证了所提方法的可行性和有效性。

In order to solve the problems of insufficient objective evaluation and lack of evaluation basis for the classification and identification of radar emitter signal,an improved gray correlation feature evaluation model combined with interval-valued intuitionistic fuzzy thought is constructed.The model introduces the dimension of signal-to-noise ratio(SNR)to examine the dynamic differences of data at different levels,describes feature information with interval data,and establishes an interval-valued intuitionistic fuzzy comprehensive decision matrix.Secondly,an optimization model that maximizes the total deviation between features is used to determine the weight of each indicator.Finally,based on the improved gray correlation framework,the ranking of feature schemes is achieved by combining with the approach to ideal points.The simulation results show that the proposed method can give the sorting identification feature evaluation and sorting results that are consistent with the actual situation,and is basically consistent with the analysis results by the unimproved gray correlation method,which verifies the feasibility and effectiveness of the proposed method.