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http://dx.doi.org/10.6109/jkiice.2013.17.5.1083

Analysis of target classification performances of active sonar returns depending on parameter values of SVM kernel functions  

Park, Jeonghyun (경북대학교)
Hwang, Chansik (경북대학교)
Bae, Keunsung (경북대학교)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.5, 2013 , pp. 1083-1088 More about this Journal
Abstract
Detection and classification of undersea mines in shallow waters using active sonar returns is a difficult task due to complexity of underwater environment. Support vector machine(SVM) is a binary classifier that is well known to provide a global optimum solution. In this paper, classification experiments of sonar returns from mine-like objects and non-mine-like objects are carried out using the SVM, and classification performance is analyzed and presented with discussions depending on parameter values of SVM kernel functions.
Keywords
sonar target classification; support vector machine(SVM); kernel function;
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