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Abstract

The rapid convergence of PPP-RTK depends on the ionospheric correction including the accuracy and prior information. However, the traditional grid-based ionospheric model often uses fixed ionospheric prior information without taking into account the spatiotemporal diversity of the ionosphere, thus weakening the performance of PPP-RTK and limiting its application scenarios. In this study, a self-validation grid-based ionospheric model is proposed to improve the performance of PPP-RTK. A grid-based slant ionospheric model adapted to multi-scale networks is developed first with the careful consideration of receiver DCBs. Additionally, the ionosphere residuals obtained by self-validation of each reference station are assigned to the regional area based on distance and time, providing more reasonable ionospheric prior information for PPP-RTK. Then, PPP-RTK can achieve fast convergence with more reasonable ionospheric prior information. Experiments conducted under different ionospheric conditions demonstrate that the modified model significantly improves both the positioning accuracy and convergence time of PPP-RTK. During the ionosphere calm period, the average convergence time is reduced from 15.4s to 4.1s and the positioning accuracy is improved by 29.96% compared with the traditional grid model. Furthermore, during the ionosphere active period, the positioning accuracy is improved from (0.08, 0.10, 0.39) m to (0.05, 0.04, 0.12) m, with the improvement of 37.50%, 60.00%, 69.23% in the east, north and up directions, respectively.