This paper presents an ensemble approach for Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) that integrates AlexNet, Support Vector Machine (SVM), and template matching through majority voting to improve classification accuracy under various operating conditions. The study utilizes the MSTAR dataset, focusing on both Standard Operating Conditions (SOC) and Extended Operating Conditions (EOC). The methodology begins with SAR image preprocessing, applying threshold segmentation with histogram equalization and morphological filtering to extract target regions. These regions undergo feature extraction, with AlexNet and SVM separately classifying the targets, while template mat... More >