Precise point positioning (PPP) based on the machine learning-based ionospheric tomography

Author:

Chen Pengxiang,Zheng Dunyong,Nie Wenfeng,Ye Fei,Long Sichun,He Changyong,Liao Mengguang,Xie Jian

Funder

Hunan Provincial Science and Technology Department

Scientific Research Foundation of Hunan Provincial Education Department

Hunan Provincial Natural Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference51 articles.

1. Austen, J.R., Franke, S.J., Liu, C.H., et al., 1986. Application of computerized tomography techniques to ionospheric research. In Proceedings of the International Beacon Satellite Symposium on Radio Beacon Contribution to the Study of Ionization and Dynamics of the Ionosphere and to Corrections to Geodesy and Technical Workshop, Oulu, Finland, pp. 25-35, Part 1.

2. The International Reference Ionosphere model: A review and description of an ionospheric benchmark;Bilitza;Rev. Geophys.,2022

3. Uncombined precise point positioning with triple-frequency GNSS signals;Cao;Adv. Space Res.,2019

4. Ionospheric Regional modeling Algorithm based on GNSS Precise Point Positioning;Chen,2021

5. Chen, T., Guestrin, C., 2016. XGBoost: A scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 785-794).

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