From mathematical to AI-based methods: A review of marine PNT data fusion and uncertainty handling

The development of accurate and reliable Positioning, Navigation, and Timing (PNT) systems increasingly depends on advancements in computer science, particularly data fusion and uncertainty handling. Scientific research in maritime navigation focuses on trajectory prediction, route planning, and collision avoidance, among other areas, whereas all mentioned topics are highly dependent on the accuracy and robustness of the provided data. However, positioning and uncertainty handling methods still face limitations, including measurement absence or inaccuracy, increased threats of spoofing and jamming attacks, and limited adaptability to dynamic maritime conditions. Previous reviews have not systematically addressed positioning accuracy, data fusion, and uncertainty handling in this context, nor have they consistently applied transparent methodologies, leaving gaps in reproducibility and coverage. This review addresses these gaps by presenting a structured synthesis of techniques to improve the accuracy and reliability of maritime navigation, ranging from traditional mathematical approaches to AI-based solutions. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines are followed to ensure methodological transparency. This review makes several unique contributions. It provides PRISMA-based systematic overview of ship positioning and uncertainty-handling methods and attempts to address key research questions, including existing solutions, challenges, and emerging opportunities. Additionally, the potential of AI to enhance navigation systems is thoroughly discussed, with future research directions to address current limitations. Together, these contributions provide a roadmap for advancing the reliability, resilience, and safety of maritime navigation. • A comprehensive review of marine data fusion for PNT solutions. • Key challenges and future opportunities regarding ship positioning are discussed. • Explores the potential of AI to improve data accuracy and reliability. • Contributes to the ongoing efforts to improve navigation precision.