Title :
Support vector machine radar emitter identification algorithm based on AP clustering
Author :
Weihua Xiao ; Hongchao Wu ; Chengzhi Yang
Author_Institution :
Dept. of Aviation Inf. Counterwork, Aviation Univ. of Air Force, Changchun, China
Abstract :
This paper designs SVM radar emitter classification and identification methods based on the AP clustering. Using AP clustering algorithm to optimize the data set obtains a high-quality, small-sample training set of SVM classifier. Experimental results show that compared with the traditional SVM classifiers, the hybrid classifier has higher classification accuracy and furthermore Radar emitter classification and identification of the method is better.
Keywords :
radar; support vector machines; affinity propagation clustering; radar emitter identification; support vector machine; Accuracy; Classification algorithms; Clustering algorithms; Educational institutions; Radar; Support vector machines; Training; AP clustering; radar emitter identification; support vector machine;
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-1014-4
DOI :
10.1109/QR2MSE.2013.6625989