###### Abstract  
With the ever-increasing volume of maritime traffic, the risks of ship navigation are becoming more significant, making the use of advanced multi-source perception strategies and AI technologies indispensable for obtaining information about ship navigation status. In this paper, first, the ship tracking system was optimized using the Bi-YOLO network based on the C2f_BiFormer module and the OC-SORT algorithms. Second, to extract the visual trajectory of the target ship without a reference object, an absolute position estimation method based on binocular stereo vision attitude information was proposed. Then, a perception data fusion framework based on ship spatio-temporal trajectory features (ST-TF) was proposed to match GPS-based ship information with corresponding visual target information. Finally, AR technology was integrated to fuse multi-source perceptual information into the real-world navigation view. Experimental results demonstrate that the proposed method achieves a mAP0.5:0.95 of 79.6% under challenging scenarios such as low resolution, noise interference, and low-light conditions. Moreover, in the presence of the nonlinear motion of the own ship, the average relative position error of target ship visual measurements is maintained below 8%, achieving accurate absolute position estimation without reference objects. Compared to existing navigation assistance, the AR-based navigation assistance system, which utilizes ship ST-TF-based perception data fusion mechanism, enhances ship traffic situational awareness and provides reliable decision-making support to further ensure the safety of ship navigation. data fusion; marine autonomous surface ships; ship traffic safety; ship recognition and tracking; machine vision; AR navigation assistance +
Footnote †: journal: Marine Science and Engineering  
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widespread attention from scholars around the world [3]. To promote the development of MASS technology, Rolls-Royce has proposed the vision of \"smart ships\", emphasizing the application of AR and data fusion technologies, which are believed to bring revolutionary progress to ship navigation systems. In line with this trend, AR technology has gradually become a key means to enhance the safety and operational efficiency of ships. Several companies and research institutions have made significant progress in integrating AR technology with the maritime sector. Specifically, the ClearCruise AR yacht navigation system, developed by the UK-based Raymarine company, captures the forward view in real time using high-definition cameras. It combines onboard sensor data and utilizes AR technology to overlay virtual information, providing decision support to the operator [4]. The HiNAS 2.0 navigation system, developed by the South Korean company Avikus, integrates AR technology. It has been successfully applied to the transoceanic navigation of the LNG ship \"Prism Courage\", significantly improving the safety and operational efficiency of autonomous ship navigation [5]. Although research on AR-assisted navigation systems in the maritime field is still in its early stages, its potential has been widely recognized. Researchers [PERSON] et al. [6], in their study of 11 AR maritime solutions, pointed out that AR technology holds significant research value in maritime applications and is expected to further optimize ship navigation, situational awareness, and decision support functions, thereby having a profound impact on the safety and efficiency of the shipping industry. Currently, mainstream ship navigation assistance systems mainly focus on visual scenarios. These systems fuse real-time perceived environmental information with heterogeneous data, such as the Automatic Identification System (AIS) [7; 8], and present key navigation information in a visual format.