Paper
27 November 2024 Performance study of real-time PPP based on broadcast ephemeris
Yucheng Zhang, Junqin Wu
Author Affiliations +
Proceedings Volume 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024); 134022I (2024) https://doi.org/10.1117/12.3048736
Event: International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 2024, Zhengzhou, China
Abstract
A real-time PPP method based on broadcast ephemeris was designed to solve the problem that IGS precision products have a certain delay and the network may be unstable in driving. Equation is deduced in this paper, based on the original observation applies to multi-frequency multi-mode under three frequency (TDF) and the ionosphere two combination model, considering the dynamic factors such as environment, data processing using the extended kalman filtering through the station observation data dynamically in imitation experiment to evaluate the proposed approach. Results show that compared with single GPS system, multiple systems on the positioning accuracy and convergence time is improved, especially at the zenith direction, from the original 5.32cm to 0.82cm, have larger ascension. Compared with the dual-frequency ionosphere-free model, although there is no significant improvement in the horizontal direction, there is a significant improvement in the zenith direction. The positioning accuracy reaches 0.82cm, although there is no significant improvement in the horizontal direction, and the zenith direction accuracy is improved by 46.4%.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yucheng Zhang and Junqin Wu "Performance study of real-time PPP based on broadcast ephemeris", Proc. SPIE 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 134022I (27 November 2024); https://doi.org/10.1117/12.3048736
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KEYWORDS
Satellites

Signal filtering

Satellite navigation systems

Data modeling

Performance modeling

Clocks

Covariance matrices

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