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).