DocumentCode
3443658
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
fYear
2013
fDate
15-18 July 2013
Firstpage
2062
Lastpage
2064
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-1014-4
Type
conf
DOI
10.1109/QR2MSE.2013.6625989
Filename
6625989
Link To Document