基于相似度的雷达目标识别灰关联分析算法

Algorithm of grey correlation analysis for radar target recognition based on similarity

针对参数重叠的雷达目标识别算法准确率较低、对复杂体制雷达目标识别效果较差的问题,提出了基于相似度的灰关联分析算法,实现对复杂体制雷达目标的融合识别。该算法首先提取各参数间的相似度矩阵,然后运用灰关联分析得出相应的灰关联系数,同时根据各参数匹配程度确定其权重值,与灰关联系数组合获得待识别信号与库信号的灰关联度,根据灰关联度完成目标识别。仿真实验结果表明,该算法能很好地降低参数重叠给识别带来的影响,提高识别正确率,快速实现复杂体制雷达目标的识别。

Acoording to the algorithm can＇t better identify complex radar targets and improve the accuracy while facing parameters overlapping, an algorithm of similarity-grey relational analysis based on similarity was proposed. Firstly, the similarity matrix between the parameters was extracted by the algorithm. And then the grey correlation analysis was used to get the corresponding grey correlation coefficient. At the same time, the weight value was determined according to the matching degree of each parameter, the grey correlation degree of the signal was identified and the library signal was obtained by combining with the grey correlation coefficient, and the target recognition was completed according to the grey correlation degree. Finally, having the grey correlation between the signal and the grey correlation coefficient, which can realize the identification of the complex radar target. The simulation results show that the impact of parame- ters overlapping with high recognition accuracy was reduced, the recognition accuracy was improved, and the identifica- tion of complex system radar targets were quickly realized by the proposed algorithm.