Geomagnetic matching cooperative positioning method for unmanned boat cluster based on factor graph

Unmanned boat clusters formed by unmanned boats may not only enhance efficiency but also improve the accuracy and stability of the overall positioning of the cluster, which is of significant research interest. The challenging offshore island environment makes GNSS susceptible to disruption from occlusion effects and signal reflection. Existing cooperative positioning methods are unable to achieve the accuracy and stability required for large-scale cluster positioning of unmanned boats. To address the aforementioned issues, this paper proposes a Geomagnetic Matching Cooperative Positioning Method for Unmanned Boat Cluster Based on Factor Graph (GUCP). The method applies geomagnetic matching technology by first using cooperative positioning based on factor graph to correct the positioning of unmanned boat clusters. It then uses the corrected positioning as the reference position for geomagnetic matching, and feeds the position estimate back to the unmanned boat clusters for the next iteration positioning. This approach eliminates the reliance on inertial navigation and enables long-term autonomous navigation and positioning of unmanned boat clusters. The results indicate that the GUCP proposed in this paper compared to existing cooperative positioning methods can enable prolonged use of unmanned boat clusters and effectively enhance the positioning accuracy and stability.