Feature Extraction and Classification of ISAR Images Based on SVM
Conference: EUSAR 2006 - 6th European Conference on Synthetic Aperture Radar
05/16/2006 - 05/18/2006 at Dresden, Germany
Proceedings: EUSAR 2006
Pages: 4Language: englishTyp: PDFPersonal VDE Members are entitled to a 10% discount on this title
Su, Fulin; Li, Shaobin; Zhang, Ye (Harbin Institute of Technology, P. R. China)
In this paper, an auto-target-recognition method based on ISAR image was presented. Three types of features were implemented, namely the Fourier coefficients, the wavelet coefficients and some shape features of the ISAR image. Also, three kinds of classifiers: nearest-neighbour, BP neural network and SVM, are considered. Experimental results showed that the Fourier coefficients with some shape features and the SVM classifier had the best discrimination and the classifcaltion precision can reach to more than 94%.