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Improving the performance of multi-LEO SLR observations processing using variance component estimation

Urheber*innen

Fu,  Yuanchen
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Zhang,  Keke
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Li,  Xingxing
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Yuan,  YongQiang
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Zheng,  Hongjie
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Lou,  Jiaqing
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Zitation

Fu, Y., Zhang, K., Li, X., Yuan, Y., Zheng, H., Lou, J. (2023): Improving the performance of multi-LEO SLR observations processing using variance component estimation, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-0643


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5016846
Zusammenfassung
For the purpose of orbit validation, currently, many low Earth orbit (LEO) satellites of Earth observation missions are equipped with laser retro-reflectors. These Satellites Laser Ranging (SLR) observations exhibit a great potential to improve the accuracy of the SLR-based terrestrial reference frame, which is only realized by spherical geodetic satellites at present. How to weigh the SLR observations collected by different LEO satellites is always a troublesome issue when processing these observations. The purpose of this study is to optimize the integration of multi-LEO satellite SLR solutions by adjusting the weights of the observations using the Helmert Variance component estimation (VCE). The SLR observations of seven LEO satellites from three typical LEO missions: GRACE-Follow-On, Swarm, and Sentinel-3, are processed. The results indicate that the coordinate accuracy of SLR stations is significantly improved by 21% after applying VCE, while the improvement for Earth pole coordinates can reach 34%. We find that classifying the observations by satellite-station pair in the VCE processing outperforms the satellite-specific or station-specific observations classification. We also investigate the impact of range bias parameterization on the VCE performance. In addition, considering a steep rise in the computational time when using VCE, we evaluate the feasibility of a simplified VCE method in SLR observation processing. The result indicates that the simplified VCE solution can present the same performance as the traditional VCE solution, but the computational efficiency is significantly improved by thirty times.