改进加权SVC的雷达信号分选新方法

New Method of Radar Signals Sorting Based on Improved Weighted SVC

目前基于多参数的雷达信号聚类分选方法得到了广泛应用,但是当雷达信号严重交叠时,存在正确率不高的问题,为此,在支持向量聚类和分层互耦的分选算法基础上,首先利用变精度粗糙集对标准化的雷达信号数据进行加权处理,然后通过分析聚类分选结果构建有效性评价模型,确定最佳的聚类分选参数。仿真表明,当雷达信号数据严重交叠时,相比原始方法,改进的方法正确率显著提高,证明了方法的有效性。

At present,multi parameter radar signal clustering is widely used,however,when the radar signals are heavily overlapped,there is a problem of low accuracy. Based on support vector clustering and delaminating coupling sorting algorithm,the standardized radar signal data are weighted by the variable precision rough set; by analyzing the results of cluster sorting,the model of effective evaluation is established; and the optimal clustering sorting parameters are determined. The simulation results show that when the radar signal data is seriously overlapped,the accuracy of the proposed method is improved greatly compared with the original method,which proves the effectiveness of the proposed method.