基于BFSN聚类的雷达信号分选与特征提取算法

Radar Signal Sorting and Feature Extraction Algorithm Based on BFSN Clustering

为克服传统信号分选算法的局限性,提出了一种雷达信号分选与特征提取相结合的算法。这种算法利用了数据挖掘中的聚类技术,可用于常规雷达和特殊雷达的信号分选。另外,该算法将信号分选与特征提取进行有机的结合,算法的结果不仅分选出雷达信号,还得到了每部雷达信号的参数特征。最后用仿真结果验证此算法的有效性。

This paper introduces an algorithm,which combines radar signal sorting with feature extraction,in order to overcome the limitation of traditional radar signal sorting algorithm.The algorithm makes use of the clustering technology of data mining,can apply to general radar and special radar.In addition,this algorithm has incorporated feature extraction with signal sorting,so the algorithm not only sorts radar signals,but also gains the parameter features of every radar signal.In the end of this paper,the simulated experiments show that the new method is effective.