航空学报 > 2025, Vol. 46 Issue (6): 531623-531623   doi: 10.7527/S1000-6893.2024.31623

基于抗差方差分量估计的多系统GNSS定位因子图优化算法

施闯1,2,3, 王智新1, 张昊4, 李团4(), 王志鹏1,2,3   

  1. 1.北京航空航天大学 电子信息工程学院,北京 100191
    2.卫星导航与移动通信融合技术工业和信息化部重点实验室,北京 100191
    3.空地一体新航行系统技术全国重点实验室,北京 100191
    4.北京理工大学 前沿交叉科学研究院,北京 100081
  • 收稿日期:2024-12-06 修回日期:2024-12-10 接受日期:2024-12-24 出版日期:2024-12-31 发布日期:2024-12-30
  • 通讯作者: 李团 E-mail:tuanli@buaa.edu.cn
  • 基金资助:
    国家重点研发计划(2023YFB3907302);北京市自然科学基金(4254104);空地一体新航行系统技术全国重点实验室开放基金(2024B21);北京理工大学研究生科研水平和创新能力提升专项(2024YCXY029)

Factor graph optimization based multi-GNSS positioning with robust variance component estimation

Chuang SHI1,2,3, Zhixin WANG1, Hao ZHANG4, Tuan LI4(), Zhipeng WANG1,2,3   

  1. 1.School of Electronics and Information Engineering,Beihang University,Beijing 100191,China
    2.Laboratory of Navigation and Communication Fusion Technology,Ministry of Industry and Information Technology,Beijing 100191,China
    3.State Key Laboratory of CNS/ATM,Beijing 100191,China
    4.Advanced Research Institute of Multidisciplinary Sciences,Beijing Institute of Technology,Beijing 100081,China
  • Received:2024-12-06 Revised:2024-12-10 Accepted:2024-12-24 Online:2024-12-31 Published:2024-12-30
  • Contact: Tuan LI E-mail:tuanli@buaa.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2023YFB3907302);Beijing Natural Science Foundation(4254104);Open Project Program of State Key Laboratory of Communication Navigation, Surveillance/Air Traffic Management(2024B21);BIT Research and Innovation Promoting Project(2024YCXY029)

摘要:

随着全球卫星导航(GNSS)技术的发展,得益于可用卫星数量的增加和更优的几何分布,多星座全球导航卫星系统定位能为用户提供更为精确的定位结果。近期研究表明,基于因子图优化(FGO)的多系统GNSS定位相较于传统算法呈现出更好的性能。然而,基于FGO的多GNSS定位随机模型的精细化及系统间自适应定权问题仍未充分研究。提出了一种基于赫尔默特方差分量估计(HVCE)的多系统GNSS定位因子图优化方法,通过系统间自适应定权进一步提升复杂城市环境中基于因子图优化的多系统GNSS定位的性能。此外,利用抗差算法IGG-Ⅲ进一步提高了HVCE及FGO状态估计的鲁棒性。在城市环境中的车载测试结果表明:相对于单一FGO方案,所提方法在北向、东向和垂直方向上的多系统GNSS定位精度分别提高了35.4%、8.7%和25.1%。总体而言,所提方法通过精细化随机模型并实现系统间自适应定权,能够在因子图优化方法的基础上进一步提升复杂城市环境中多系统GNSS的定位性能。

关键词: 多系统GNSS定位, Helmert方差分量估计, 抗差算法, 自适应定权, 因子图优化

Abstract:

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 proposed algorithm is validated to be an effective approach to improving multi-GNSS performance in complex urban environments by refining the stochastic model and adaptively weighting the measurements.

Key words: multi-GNSS positioning, Helmert Variance Component Estimation (HVCE), robust algorithm, adaptive weighting, factor graph optimization

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