Multi-parameter Radar Signal Sorting Method Based on Fast Support Vector Clustering and Similitude Entropy

The radar signal sorting method based on traditional clustering algorithm takes on a high time complexity and has poor accuracy. Considering the issue, a new sorting method is researched based on Cone Cluster Labeling (CCL) method for Support Vector Clustering (SVC) algorithm. The CCL method labels cluster in data space, and therefore avoides the high complexity caused by the calculation of adjacency matrix in feature space. This method is introduced into the radar signal sorting and it is modified for lower complexity and high accuracy by handling the outliers. Meanwhile a new cluster validity index, Similitude Entropy (SE) index, is proposed which assesses the compactness and separation of clusters using information entropy theory. Experimental results show that the strategy can improve efficiency without sacrificing sorting accuracy.