Synthetic Aperture Radar (SAR) Systems are high-tech radar systems with the ability to create long-range high resolution images for day/night and all weather conditions for discovery/surveillance purposes. The images obtained from these systems can be used for target recognition with various pattern recognition and image processing methods. In this study, intense speckle noise in the SAR images of different military vehicle types was reduced by various filtering and thresholding methods. From the pre-processed images, feature extraction was performed by using Gabor filters. In the classification phase, using the sparse representation method, the high recognition accuracy is obtained from SAR images of different vehicle types. In addition, sparse representation method is superior to Naive Bayes and KNN(k nearest neighbor), which are also used in classification stage.