Abstract: We propose a method for synthetic aperture radar images target discrimination based on the principal component analysis and an approach combining support vector machine (SVM) and linear discriminant analysis(LDA). Dimensionality of the image vector is reduced and the global features are extracted by using principal component analysis. The global features are transformed and the results are used to generate classifiers which complete target discrimination. The results show the high performance of the proposed method.

Key words: synthetic aperture radar (SAR), principal component analysis (PCA), linear discriminant analysis (LDA), support vector machine (SVM), discrimination