Study on SAR target recognition based on Support Vector Machine

Author

Tao, Wu ; Xi, Chen ; Xiangwei, Ruang ; Lei, Niu

Author_Institution

No.38 Res. Inst., China Electron. Technol. Corp., Hefei, China

fYear

2009

fDate

26-30 Oct. 2009

Firstpage

856

Lastpage

859

Abstract

This paper studies MSTAR SAR target recognition with Support Vector Machine (SVM) classifier by using Principal Component Analysis (PCA) features, without consideration of errors in target aspect angle estimation. A good strategy is proposed to avoid errors in classifier selection for the errors in estimation of aspect angle. The experiments based on MSTAR data set show perfect results.

Keywords

principal component analysis; radar target recognition; support vector machines; synthetic aperture radar; MSTAR SAR; PCA; SAR target recognition; SVM; angle estimation; principal component analysis; support vector machine; Constraint optimization; Error correction; Estimation error; Image recognition; Image segmentation; Principal component analysis; Radar imaging; Support vector machine classification; Support vector machines; Target recognition; PCA; SVM; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Synthetic Aperture Radar, 2009. APSAR 2009. 2nd Asian-Pacific Conference on

Conference_Location

Xian, Shanxi

Print_ISBN

978-1-4244-2731-4

Electronic_ISBN

978-1-4244-2732-1

Type

conf

DOI

10.1109/APSAR.2009.5374190

Filename

5374190

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2981361