Density-Based Fuzzy C-Means Multi-center Re-clustering Radar Signal Sorting Algorithm

Abstract

As the improving strategic position of electronic warfare in modern warfare, radar sorting detection becomes the eye of modern information warfare and plays an important role in it. This paper designs a new pulse radar sorting algorithm: a Density-Based Fuzzy C-Means Multi-Center Re-Clustering (DFCMRC) radar signal sorting algorithm. This algorithm mainly combines the advantages of Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm and Fuzzy C-means (FCM) clustering algorithm. This paper also optimizes the structure of the DFCMRC algorithm, which changes the algorithm that randomly generated the initial center point to the Clustering by Fast Search and Find of Density Peaks (CFSFDP) algorithm. After comparison tests, the DFCMRC algorithm sorting result is better than the K-means algorithm, the DBSCAN algorithm and the FCM algorithm. Also, the membership grade description of DFCMRC makes more sense than the FCM's. Accelerated optimized DFCMRC algorithm can reduce more than half iterations, which greatly shortens the algorithm calculation time.