Multi-factor Fuzzy Fusion Algorithm for Radar and AIS Data Integration

The multi-factor fuzzy algorithm-based fusion method for radar and AIS data integration is a multi-source data combination approach that enhances the accuracy and reliability of maritime traffic monitoring. The core concept involves fusing radar and AIS data while employing a multi-factor fuzzy algorithm to process the integrated dataset for more precise results. This methodology comprehensively considers the distinct characteristics of radar and AIS data, including factors such as data precision, reliability, and real-time performance. In the implementation, the algorithm typically involves defining multiple fuzzy membership functions to quantify data quality metrics. Key technical aspects include: - Establishing fuzzy rules to handle data conflicts and uncertainties - Implementing temporal and spatial correlation algorithms for data alignment - Designing adaptive weighting mechanisms based on dynamic confidence levels The fusion process incorporates critical elements like spatiotemporal relationships and dynamic weight allocation to ensure result accuracy and reliability. This approach demonstrates significant application potential in maritime traffic surveillance and related domains.