The Automatic Identification System (AIS) has become essential for enhancing navigation safety and enabling innovative maritime applications. However, current research often relies on individual AIS data sources, limiting the comprehensiveness of maritime monitoring. This paper aims to develop a data fusion model that integrates AIS data from both fixed stations and satellite sources. Using a multi-sensor fusion approach, the model applies timestamp annotation, deduplication, and message decoding to AIS messages. Results demonstrate improved spatial and temporal coverage, supporting enriched situational awareness in maritime environments. This scalable model lays the foundation for advanced maritime monitoring and decision-making.