Space-based Global Maritime Surveillance. Part I: Satellite Technologies
Giovanni Soldi, Domenico Gaglione, Nicola Forti, Alessio Di Simone,, Filippo Cristian Daffin\`a, Gianfausto Bottini, Dino Quattrociocchi, Leonardo, M. Millefiori, Paolo Braca, Sandro Carniel, Peter Willett, Antonio Iodice,, Daniele Riccio, and Alfonso Farina

TL;DR
This paper reviews satellite sensor technologies for maritime surveillance, highlighting their advantages and limitations, to enhance global maritime monitoring when terrestrial systems are insufficient.
Contribution
It provides a comprehensive overview of space-based sensor technologies for maritime surveillance, emphasizing their role in complementing ground-based systems.
Findings
Satellite sensors like AIS, SAR, optical sensors, and GNSS reflectometry are crucial for comprehensive maritime monitoring.
Each satellite technology has specific advantages and limitations for maritime surveillance.
Space-based sensors significantly enhance maritime security and monitoring capabilities.
Abstract
Maritime surveillance (MS) is crucial for search and rescue operations, fishery monitoring, pollution control, law enforcement, migration monitoring, and national security policies. Since the early days of seafaring, MS has been a critical task for providing security in human coexistence. Several generations of sensors providing detailed maritime information have become available for large offshore areas in real time: maritime radar sensors in the 1950s and the automatic identification system (AIS) in the 1990s among them. However, ground-based maritime radars and AIS data do not always provide a comprehensive and seamless coverage of the entire maritime space. Therefore, the exploitation of space-based sensor technologies installed on satellites orbiting around the Earth, such as satellite AIS data, synthetic aperture radar, optical sensors, and global navigation satellite systems…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
