Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction

doi:10.3390/rs17101792

	Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction
	Ning, Bokun 1; Zhao, Fang 1; Luo, Haiyong 2; Luo, Dan 3; Shao, Wenhua 1
	2025-05-21
发表期刊	REMOTE SENSING
卷号	17 期号:10 页码:22
摘要	The combination of GNSS RTK and INS offers complementary advantages but faces significant challenges in urban canyons. Frequent cycle slips in carrier phase measurements and ambiguity resolution algorithms increase computational burden without improving positioning accuracy. Additionally, environmental interference introduces noise into observations, potentially leading to complete signal loss. To address these issues, this paper proposes a factor graph optimization (FGO) positioning algorithm incorporating predictive observation factors. First, a penalized spline (P-spline) is constructed to predict and smooth Doppler measurements. The predicted Doppler is then fused with the dynamics model predictions to enhance robustness. Using predictive Doppler, carrier phase and pseudorange observations are reconstructed, generating predictive constraint factors to improve positioning accuracy. Real-world tests conducted in urban canyons, including Shanghai, demonstrate that the proposed method maintains stable positioning performance even under short-term signal outages, effectively mitigating cumulative positioning errors caused by data loss. Compared to traditional methods that rely solely on available observations, the proposed algorithm improves northward and dynamic positioning accuracy by 35% and 29%, respectively, providing a highly robust navigation solution for complex urban environments.
关键词	P-spline factor graph optimization (FGO) time-difference carrier phase (TDCP) IMU pre-integration Doppler prediction
DOI	10.3390/rs17101792
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China ; [62261042]
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001496037600001
出版者	MDPI
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/42412
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Luo, Haiyong
作者单位	1.Beijing Univ Posts & Telecommun, Sch Comp Sci, Beijing 100876, Peoples R China 2.Chinese Acad Sci, Beijing Key Lab Mobile Comp & Pervas Device, Inst Comp Technol, Beijing 100190, Peoples R China 3.Beijing Forestry Univ, Sch Informat Sci & Technol, Beijing 100083, Peoples R China
推荐引用方式 GB/T 7714	Ning, Bokun,Zhao, Fang,Luo, Haiyong,et al. Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction[J]. REMOTE SENSING,2025,17(10):22.
APA	Ning, Bokun,Zhao, Fang,Luo, Haiyong,Luo, Dan,&Shao, Wenhua.(2025).Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction.REMOTE SENSING,17(10),22.
MLA	Ning, Bokun,et al."Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction".REMOTE SENSING 17.10(2025):22.