基于抗差方差分量估计的多系统 GNSS 定位因子图优化算法

With the development of Global Navigation Satellite System（GNSS），multi-GNSS positioning has been shown to provide a more effective solution for accurate localization，benefiting from an increased number of available satellites and improved geo-metric distribution. Recent research indicates that Factor Graph Optimization （FGO）based multi-GNSS positioning outperforms traditional algorithms. However，the refinement of the stochastic model and the adaptive weighting of FGO-based multi-GNSS positioning remain underexplored. We propose a robust Helmert Variance Component Estimation（HVCE）method to further enhance the performance of multi-GNSS positioning in challenging urban scenarios by adaptive weighting for multi-GNSS. Additionally，the robust algorithm IGG-III is applied to improve both the robustness of the HVCE method and the state estimation within the FGO framework. The results of vehicle-borne tests show that compared with the single FGO scheme，the proposed algorithm improves positioning accuracy by 35. 4%，8. 7%，and 25. 1% in the north，east，and vertical directions，respectively. Overall，the pro- posed algorithm is validated to be an effective approach to improving multi-GNSS performance in complex urban envi- ronments by refining the stochastic model and adaptively weighting the measurements.