Ocean Object Surveillance Using Satellite Synthetic Aperture Radar

Satellite Synthetic Aperture Radar (SAR) has long been a key technology for ocean observation, due to its all-weather, day-and-night imaging capability. It plays a vital role in closing critical gaps in marine monitoring, supporting applications such as maritime navigation safety, illegal fishing detection, offshore infrastructure protection, and marine pollution response. As global marine economic activity expands and maritime security challenges grow more complex, the need for accurate, efficient, and scalable ocean object surveillance is becoming increasingly urgent. In parallel, rapid advances in artificial intelligence (AI) and related techniques are opening new avenues for SAR-based monitoring, offering the potential to overcome traditional limitations in data volume, processing speed, and detection performance. This evolving landscape creates a timely opportunity to rethink how SAR is used for operational ocean surveillance.

This Research Topic aims to advance the operational use of SAR-based ocean object surveillance by harnessing emerging technological developments, particularly in artificial intelligence. It focuses on addressing key challenges in real-world marine surveillance, including the accurate detection of small or moving targets under complex sea states, the efficient processing of large-scale SAR datasets, and the robust integration of SAR observations with other monitoring systems.

We seek contributions that demonstrate how innovative algorithms, models, and system designs can enhance SAR’s capabilities and translate into tangible benefits for maritime management. By collecting cutting-edge methods, validation studies, and practical case applications, this Research Topic intends to narrow the gap between technical innovation and field deployment. The ultimate goal is to support smarter maritime regulation, risk assessment, and emergency response, and to contribute to safer, more resilient, and more sustainable marine environments and economies.

This Research Topic focuses on the application scenarios and interdisciplinary development of SAR-based ocean object surveillance. We welcome contributions that address, but are not limited to, the following themes:

Application of emerging technologies (e.g., AI, machine learning, deep learning) to optimize SAR data processing for marine target detection, tracking, and classification.

Case studies showing how SAR-based surveillance, enhanced by AI or related tools, informs maritime policies, regulatory decisions, or industrial practices.

Integration of SAR with multi-source data (e.g., AIS, optical remote sensing, in situ observations) using novel methods to improve surveillance accuracy, robustness, and usability.

Assessment of the social, economic, and environmental impacts or benefits of AI-enhanced SAR surveillance in marine management and governance.

Development and evaluation of region-specific SAR-based surveillance strategies, including AI-supported approaches tailored to diverse sea states and operational conditions.

We encourage the submission of original research articles, reviews, methodological papers, and application-oriented case studies.