Classification of Underwater Mines by Means of the FRFT and SVM

摘要：

Classification by acoustic echoes analysis of buried sea mines is the main focus of this paper. Both simulation and actual experiment data show that when the active sonar transmits chirp signal, the energy of buried mines and reverberation echoes will concentrate on different fractional domain, which results the very different properties between the fractional Fourier spectrum of target echoes and that of reverberation. Features are extracted by means of the FRFT (Fractional Fourier Transform) spectrum, and then the Karhunen-Loeve (K-L) transform is used to compress the features before sending to classification. A SVM (Support Vector Machine) classifier is trained and tested on the feature sets of both target and reverberation samples. Experiment results of the FRFT method under different elevations indicated good recognition and classification rates.

关键词： FRFT feature extraction K-L transform SVM

作者: Li Tingting Li Xiukun Xia Zhi

作者单位: National Laboratory of Underwater Acoustic Technology Harbin Engineering UniversityHarbin,Heilongjia National Laboratory of Underwater Acoustic Technology Harbin Engineering University Harbin,Heilongji

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-6

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）