Homogeneous Network-RTK Correction Residual Modeling Techniques for Improving the User Positioning Performance

Yunho Cha, Cheolsoon Lim, Yebin Lee, Yongrae Jo, Byungwoon Park, Junesol Song

Abstract:	Real-Time Kinematics (RTK) is a precise relative positioning technique which uses carrier phase measurements of satellite signals. This method enables users to determine their position with high precision by resolving the integer ambiguity of the phase measurement with mm-level noise. However, there is an inherent limitation: it remains valid only within a specific distance, typically about 10km, from a reference station. To overcome this limitation, researchers are actively working on Network RTK, which extends the baseline by networking multiple reference stations. Network RTK can be largely categorized into VRS (Virtual Reference Station), FKP (Flächen Korrektur Parameter), and MAC (Master Auxiliary Concept) approaches (Takac & Zelzer, 2008). The FKP concept models dispersive and non-dispersive errors as 1st order planes after dividing the signal errors into the two components. The FKP-based error plane method facilitates the effective mitigation of spatial decorrelation in both ionospheric and geometric errors. Nevertheless, it is important to recognize that modelling these errors as 1st order planes may not perfectly describe the spatial variation of the errors, potentially leading to the presence of higher-order residual errors. In this study, we define the FKP-modeling residuals as the discrepancies between actual observable errors and FKP corrections, and model them as 2nd order curved planes. To validate this methodology, we conducted experiments using real reference station observation data. Furthermore, we introduce practical applications of these modeling residual terms as examples for enhancing positioning accuracy and estimating Network RTK position uncertainty levels.
Published in:	Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023) September 11 - 15, 2023 Hyatt Regency Denver Denver, Colorado
Pages:	2539 - 2549
Cite this article:	Cha, Yunho, Lim, Cheolsoon, Lee, Yebin, Jo, Yongrae, Park, Byungwoon, Song, Junesol, "Homogeneous Network-RTK Correction Residual Modeling Techniques for Improving the User Positioning Performance," Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 2539-2549. https://doi.org/10.33012/2023.19209
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