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Performance of Three Atmospheric Density Models on Precise Orbit Determination for Haiyang-2A Satellite Using DORIS Data

  • Qiaoli Kong
  • Jinyun Guo
  • Litao Han
  • Yi Shen
Conference paper
Part of the Sustainable Civil Infrastructures book series (SUCI)

Abstract

DORIS has become a matured space geodetic technique after more than ten years of development. This geodetic technique is mainly applied to determine the orbit for the low Earth orbit (LEO) satellite. There are a number of non-conservative forces acting on Haiyang-2A (HY-2A) satellite with altitude of about 970 km, in which the atmospheric drag is the most dominant and uncertainty in the precise orbit determination (POD) with the dynamic method. In order to achieve POD for HY-2A, MSIS-86, Jacchia 1971 and DTM87 models were evaluated in this study. The precise orbits of HY-2A from DORIS data were compared with the precise orbit ephemeris computed by the Centre National d’Etudes Spatiales (CNES). Tests demonstrated that the relative optimal atmospheric density model was the empirical MSIS-86 model for HY-2A satellite with the corresponding drag coefficient of 2.0. The RMS of orbit difference between the derived orbits using MSIS-86 and the CNES orbits was 0.842 cm in the radial direction, and 3.899 cm in three dimensions (3D). This study will provide valuable references for the LEO satellites with similar altitude and surface, especially for the other HY-2 series satellite of China.

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 41704015, 41774001), A Project of Shandong Province Higher Educational Science and Technology Program (J17KA077), the Public Benefit Scientific Research Project of China (Grant No. 201412001), International Science and Technology Cooperation Program of China (Grant No. 2009DFB00130), the Basic Science and Technology Research Project of China (Grant No. 2015FY310200), and Open Fund of Engineering Laboratory of Spatial Information Technology of Highway Geological Disaster Early Warning in Hunan Province (Changsha University of Science & Technology) (Grant No. kfj150605).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Qiaoli Kong
    • 1
    • 2
    • 3
  • Jinyun Guo
    • 1
    • 2
  • Litao Han
    • 1
  • Yi Shen
    • 1
  1. 1.College of GeomaticsShandong University of Science and TechnologyQingdaoChina
  2. 2.State Key Laboratory of Mining Disaster Prevention and Control Co-Founded by Shandong Province and the Ministry of Science and TechnologyShandong University of Science and TechnologyQingdaoChina
  3. 3.Engineering Laboratory of Spatial Information Technology of Highway Geological Disaster Early Warning in Hunan ProvinceChangsha University of Science & TechnologyChangshaChina

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