Radar HRRP classification with support vector machines

The SVM (support vector machine) has good generalization property and is proven to be a powerful classification method to a wide variety of applications. In this paper, the SVM classification method is applies to the HRRP (high resolution range profile) classification problem. Furthermore, we propose a preprocessing method and present a new SVM model selection method, the combined leave-one-out cross-validation scheme with VC bound method. Accordingly, the SVM classifiers for five aircraft are designed. Their anti-noise performance and tolerance to aspect variation are compared with that of MCM (maximum correlation method). The experimental results indicate that the preprocessing procedure and model selection method are effective and the SVM method has potential in radar complex target classification