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LEO-Enhanced GNSS/INS Tightly Coupled Integration Based on Factor Graph Optimization in the Urban Environment

文献类型：期刊论文

作者Zhang, Shixuan3,4,5; Tu, Rui2; Gao, Zhouzheng1; Zou, Decai3,4,5; Wang, Siyao3,5; Lu, Xiaochun3,4,5
刊名REMOTE SENSING
出版日期2024-05-01
卷号16期号:10页码:22
关键词Global Navigation Satellite Systems (GNSS) Inertial Navigation System (INS) Low Earth Orbit (LEO) extended Kalman filter (EKF) factor graph optimization (FGO) tightly coupled integration (TCI)
DOI10.3390/rs16101782
英文摘要Precision point positioning (PPP) utilizing the Global Navigation Satellite System (GNSS) is a traditional and widely employed technology. Its performance is susceptible to observation discontinuities and unfavorable geometric configurations. Consequently, the integration of the Inertial Navigation System (INS) and GNSS makes full use of their respective advantages and effectively mitigates the limitations of GNSS positioning. However, the GNSS/INS integration faces significant challenges in complex and harsh urban environments. In recent years, the geometry between the user and the satellite has been effectively improved with the advent of lower-orbits and faster-speed Low Earth Orbit (LEO) satellites. This enhancement provides more observation data, opening up new possibilities and opportunities for high-precision positioning. Meanwhile, in contrast to the traditional extended Kalman filter (EKF) approach, the performance of the LEO-enhanced GNSS/INS tightly coupled integration (TCI) can be significantly improved by employing the factor graph optimization (FGO) method with multiple iterations to achieve stable estimation. In this study, LEO data and the FGO method were employed to enhance the GNSS/INS TCI. To validate the effectiveness of the method, vehicle data and simulated LEO observations were subjected to thorough analysis. The results suggest that the integration of LEO data significantly enhances the positioning accuracy and convergence speed of the GNSS/INS TCI. In contrast to the FGO GNSS/INS TCI without LEO enhancement, the average enhancement effect of the LEO is 22.16%, 7.58%, and 10.13% in the north, east, and vertical directions, respectively. Furthermore, the average root mean square error (RMSE) of the LEO-enhanced FGO GNSS/INS TCI is 0.63 m, 1.21 m, and 0.85 m in the north, east, and vertical directions, respectively, representing an average improvement of 41.91%, 13.66%, and 2.52% over the traditional EKF method. Meanwhile, the simulation results demonstrate that LEO data and the FGO method effectively enhance the positioning and convergence performance of GNSS/INS TCI in GNSS-challenged environments (tall buildings, viaducts, underground tunnels, and wooded areas).
WOS关键词PERFORMANCE ANALYSIS ; NAVIGATION SYSTEM ; ACCURACY
资助项目National Natural Science Foundation of China
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001231599700001
出版者MDPI
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://210.72.145.45/handle/361003/14618]  
专题国家授时中心_导航与通信研究室
通讯作者Tu, Rui
作者单位1.China Univ Geosci Beijing, Sch Land Sci & Technol, Beijing 100083, Peoples R China
2.Shandong Univ Sci & Technol, Coll Geodesy & Geomat, Qingdao 266590, Peoples R China
3.Chinese Acad Sci, Key Lab Time Reference & Applicat, Shu Yuan Rd, Xian 710600, Peoples R China
4.Univ Chinese Acad Sci, Yu Quan Rd, Beijing 100049, Peoples R China
5.Chinese Acad Sci, Natl Time Serv Ctr, Shu Yuan Rd, Xian 710600, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Shixuan,Tu, Rui,Gao, Zhouzheng,et al. LEO-Enhanced GNSS/INS Tightly Coupled Integration Based on Factor Graph Optimization in the Urban Environment[J]. REMOTE SENSING,2024,16(10):22.
APA Zhang, Shixuan,Tu, Rui,Gao, Zhouzheng,Zou, Decai,Wang, Siyao,&Lu, Xiaochun.(2024).LEO-Enhanced GNSS/INS Tightly Coupled Integration Based on Factor Graph Optimization in the Urban Environment.REMOTE SENSING,16(10),22.
MLA Zhang, Shixuan,et al."LEO-Enhanced GNSS/INS Tightly Coupled Integration Based on Factor Graph Optimization in the Urban Environment".REMOTE SENSING 16.10(2024):22.

入库方式： OAI收割

来源：国家授时中心

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