Abstract:

To enhance the correct rate that support vector clustering (SVC) processes radar emitter signal samples with complex and uneven distributions, a novel unsupervised clustering method combining editing nearest neighbor, K-nearest neighbor with SVC is presented. SVC is first employed to cluster unknown samples. Then wrong clusters are edited by using editing rules. Finally a K-nearest neighbor is introduced to classify the edited samples in terms of different distributions of known classes in a weighted way. Experiments conducted on IRIS data and radar emitter signals show that the proposed method can balance local distributions of samples and obtain the best global clustering.