An Overview of Polarized Synthetic Aperture Radar Ship Detection: From traditional methods to artificial intelligence

Synthetic aperture radar (SAR) has been widely used in marine environment research because of its unique advantages of all-day and all-weather continuous observation. Marine target detection based on SAR image data is of great significance for marine carbon emission statistics, oil spills, and marine accident emergencies. After decades of development, a large number of excellent algorithms have been accumulated in this field. However, there remains a lack of comprehensive summaries in the field that cover polarimetric SAR (PolSAR) target detection from fundamental theory to detection algorithms. This article aims to address this gap by providing a comprehensive overview and perspective of PolSAR target detection algorithms. Specifically, the historical development and current application status of PolSAR are reviewed, the fundamental theories of PolSAR are introduced, the principles of PolSAR target detection are examined, and the existing PolSAR target detection algorithms are comprehensively summarized. Additionally, challenges in current research are outlined, and three promising research directions are proposed. We hope that this compilation and classification of target detection algorithms will provide researchers with a foundational framework for understanding the current state of PolSAR target detection research and the challenges that lie ahead.