AIS Matcher: A Precise Matching Method of SAR Imagery and AIS Vessel Data for Maritime Object Identification = AIS Matcher: A Precise Matching Method of SAR Imagery and AIS Vessel Data for Maritime Object Identification

다국어 초록 (Multilingual Abstract)

This study proposes AIS Matcher, a precise matching methodology that integrates Synthetic Aperture Radar (SAR) imagery and Automatic Identification System (AIS) vessel data for enhanced maritime object identification. In conventional maritime surveillance workflows, SAR-based vessel detection and AIS-based positional information are typically processed independently, making cross-validation difficult and limiting the operational effectiveness of fused data utilization. Focusing on the complementary characteristics of the two sensors, this research presents an algorithm that matches vessel candidate regions (bounding boxes) extracted from SAR imagery with AIS trajectories through a multi-dimensional feature framework that includes spatial proximity (distance), temporal synchronization, geometric attributes (length and width), and heading direction. Unlike traditional approaches that rely solely on spatial proximity, the proposed method employs a weighted score-based matching mechanism that integrates distance, geometric similarity, and heading consistency, enabling stable candidate discrimination across diverse maritime environments. In real-world scenarios, multiple AIS signals may fall within the same SAR detection region, or some vessels may not transmit AIS at all, resulting in challenges such as multi-AIS ambiguity and missing matches. To address these issues, this study incorporates an intuitive verification interface that allows analysts to manually review uncertain cases, enhancing transparency in the matching process and enabling efficient post-processing even for large-scale datasets. Experiments conducted using commercial SAR imagery and real AIS logs collected across various sea regions demonstrate that the proposed method delivers consistent matching performance, with confirmed applicability even in high-density vessel traffic areas. The outcomes of this research offer significant potential for applications such as non-cooperative vessel tracking, illegal fishing monitoring, maritime safety management, and national security surveillance. By refining maritime situational awareness through SAR-AIS sensor fusion, AIS Matcher is expected to serve as a key component in next-generation intelligent maritime surveillance platforms.