Novel and Comprehensive Approach for the Feature Extraction and Recognition Method Based on ISAR Images of Ship Target

This paper proposes a novel and comprehensive method of automatic target recognition based on real ISAR images with the aim to recognize the non-cooperative ship targets. The special characteristics of the ISAR images for the real data compared with the simulated ISAR images are analyzed firstly. Then, the novel technique for the target recognition is proposed, and it consists of three steps, including the preprocessing, feature extraction and classification. Some segmentation and morphological methods are used in the preprocessing to obtain the clear target images. Then, six different features for the ISAR images are extracted. By estimating the features' conditional probability, the effectiveness and robustness of these features are demonstrated. Finally, Fisher's linear classifier is applied in the classification step. The results for the all-feature space are provided to illustrate the effectiveness of the proposed method.