Enhancing Vessel Operational Safety and Security through Cross-Layer Data Fusion: A Reliability Oriented Maritime Surveillance Framework

Abstract

Ensuring the operational safety of vessels and offshore infrastructure has become increasingly complex due to hybrid maritime threats, fragmented sensing coverage, and vulnerabilities in vessel identification mechanisms. Conventional single-layer monitoring approaches are insufficient to provide reliable and timely situational awareness for safety-critical maritime operations under dynamic and uncertain conditions.
To address these challenges, this study develops a heterogeneous multi-layer (HML) maritime surveillance architecture that integrates satellite-based SAR and optical sensing for wide-area monitoring, UAV and aerostat platforms for rapid tactical verification, and surface-layer systems including AIS, VHF, and LoRa-enabled maritime IoT sensors for continuous vesselstate observation. A cross-layer data fusion framework is introduced to enhance temporal consistency, spatial alignment, and information credibility across heterogeneous sensing sources. In addition, analytical models are formulated to evaluate system-level responsiveness and to quantify AIS identity integrity using a probabilistic consistency-based assessment scheme. The proposed framework is examined through four representative safety-critical maritime scenarios, including illegal oil discharge monitoring, vessel identity inconsistency detection, night-time illicit activity verification, and grounding risk assessment. The results indicate that the integrated architecture effectively mitigates the limitations of individual sensing layers, reduces uncertainty through cross-layer validation, and enables earlier and more reliable operational responses in complex maritime environments.
This work emphasizes system-level reliability and operational decision support rather than detection accuracy, demonstrating that cross-layer consistency plays a critical role in enhancing maritime safety. The proposed framework provides a scalable and engineering-oriented foundation for next-generation maritime surveillance systems and digitalized safety management in ship and offshore operations.