摘要
通过改进CFSFDP聚类方法对雷达信号进行预分选,针对原始CFSFDP方法对截断距离敏感的问题,提出直方图均衡化方法对局部密度进行均衡化,提升聚类结果鲁棒性;针对雷达信号参数交叠严重、密度分布不均衡问题,提出改进的可达距离计算方法及改进的类别分配机制,提升对复杂数据的聚类能力。通过仿真数据集及UCI标准数据集进行实验验证,采用调整兰德系数(ARI)、调整互信息(AMI)和F1-measure值对聚类结果进行评价,结果表明所提方法可有效处理复杂参数分布数据,相较于原始CFSFDP方法及经典聚类方法(DBSCAN,AP,K-means, OPTICS),聚类性能得到了提升。
The improved Clustering by Fast Search and Find of Density Peaks(CFSFDP)method is used for radar signal pre-sorting.To solve the problem that the original CFSFDP method is sensitive to the cut-off distance a method about histogram equalization is proposed to equalize the local density which improves the robustness of clustering results.In view of the serious overlapping of radar signal parameters and unbalanced density distribution an improved reachable distance calculation method and an improved clustering category assignment mechanism are proposed to improve the clustering performance on complex data sets.Through experiments on simulation data set and UCI data sets the clustering results are evaluated by ARI AMI and F1-measure.The results show that the proposed method can effectively deal with datasets with complex signal parameter distribution and has better clustering performance compared with the original CFSFDP method and classic clustering methods(DBSCAN AP K-means OPTICS).
作者
韩佳宝
崔天舒
李志豪
黄永辉
安军社
HAN Jiabao;CUI Tianshu;LI Zhihao;HUANG Yonghui;AN Junshe(Key Laboratory of Electronics and Information Technology for Space System National Space Science Center Chinese Academy of Sciences, Beijing 100000 China;University of Chinese Academy of Sciences ,Beijing 100000 China;Beijing National Research Center for Information Science and Technology Tsinghua University ,Beijing 100000 China)
出处
《电光与控制》
CSCD
北大核心
2024年第4期92-97,共6页
Electronics Optics & Control
基金
中国科学院复杂航天系统电子信息技术重点实验室自主部署基金(Y42613A32S)。
关键词
雷达信号分选
聚类
密度峰值
直方图均衡化
radar signal sorting
clustering
density peak
histogram equalization
