DocumentCode :
508654
Title :
A radar target recognition method based on auto-correlation wavelet SVM
Author :
Jie Wu ; Jianjiang Zhou ; Qiangye Gao
Author_Institution :
Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
fYear :
2009
fDate :
20-22 April 2009
Firstpage :
1
Lastpage :
4
Abstract :
Radar high-resolution range profile (HRRP) provides potentially discriminative information on the geometry of target, which has been shown to be promising signatures for radar Automatic Recognition (ATR) application. In this paper, a radar target recognition method based on auto-correlation wavelet support vector machine (AWSVM) is proposed. As the kernel of AWSVM, the auto-correlation of a compactly supported wavelet satisfies the translation invariant property, which is very important for radar ATR with HRRP. The theoretical analysis and simulation results have shown that the new algorithm is effective, the average recognition rate of five airplanes is 97.6%, and the high recognition rate is comparatively steady when the wavelet scale factor is changed in a certainty range.
Keywords :
object detection; support vector machines; target tracking; wavelet transforms; autocorrelation wavelet SVM; automatic recognition; radar high resolution range profile; radar target recognition; support vector machine; wavelet scale factor; High-resolution range profile; Radar automatic target recognition; Support vector machine; Wavelets;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Radar Conference, 2009 IET International
Conference_Location :
Guilin
ISSN :
0537-9989
Print_ISBN :
978-1-84919-010-7
Type :
conf
Filename :
5367518
Link To Document :
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