The Grid-based Regional Slant Ionospheric Model with Sufficient Corrections

Sijie Lyu, Yan Xiang, Xingyu Chen, Wenxian Yu

Peer Reviewed

Abstract: Ionospheric corrections are the most significant dependence of the PPP-RTK. It is common practice to apply the regional slant ionospheric model (RSIM) for providing more precise information than the vertical one. For the conventional RSIM, only satellites tracked by the same set of reference stations are involved to deliver the network corrections for keeping the same receiver-related biases. It decreases the number of observable satellites and weakens the performance of PPP-RTK. Therefore, in this paper, a modified RSIM is proposed to recover ionospheric corrections based on information from nearby stations. Indeed, we explored effective strategies to transfer datum between satellites, thereby preferring multi satellites with high elevation as well as long epochs of ambiguity resolution. Then, the number of available satellites between the modified and conventional RSIM is compared. Results show that the modified model transmits ionospheric corrections with a greater number of satellites at a ratio of 93%. Static tests are carried out to test the positioning performance. Compared with conventional RSIM, the modified RSIM constraints achieved faster convergence and the positioning accuracy at the east, north, and vertical parts at the first 1 min are reduced from 0.052, 0.037, and 0.152 m to 0.029, 0.026, and 0.074 m, respectively.
Published in: Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022)
September 19 - 23, 2022
Hyatt Regency Denver
Denver, Colorado
Pages: 3139 - 3149
Cite this article: Lyu, Sijie, Xiang, Yan, Chen, Xingyu, Yu, Wenxian, "The Grid-based Regional Slant Ionospheric Model with Sufficient Corrections," Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022), Denver, Colorado, September 2022, pp. 3139-3149. https://doi.org/10.33012/2022.18347
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