Calculating High Frequency Earth Rotation Parameters Using GPS Observations and Precision Analysis

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 437)

Abstract

The earth rotation parameters (ERP) have a strong correlation with the migration and movement of earth materials, extraterrestrial world gravity and the load deformation of solid earth. On the other hand, ERP is a very important parameter when converting the earth reference system to the celestial reference system. But the International Earth Rotation Service(IERS) and International GNSS Service(IGS) only release one ERP per day which cannot satisfy the user who need the high frequency of ERP. However, there are amounts of Global Positioning System(GPS) data which can be used to estimate ERP with high time resolution and long time span. Based on this, global uniformly distributed 40 IGS stations are selected to estimate ERP by using the data of the Day of Year(DOY) from 1 to 180 of 2015 with Bernese soft 5.0. In the first part, 24 h resolution of ERP is estimated. The precision of polar motion \( x_{p} \), \( y_{p} \) can be achieved at the precision 0.289, 0.245 mas while the precision of UT1-UTC can be achieved at 0.0342 ms which are made a difference with the results of IGS. In the last part of the paper, the 2 h resolution of ERP are estimated and high frequency time series are got. The precision of high frequency polar motion \( x_{p} \), \( y_{p} \) can be achieved at the precision 0.754, 0.688 mas and the precision of high frequency UT1-UTC can be achieved at 0.1050 ms which are made a difference with the results of IGS at UTC 12:00. The high frequency results have lower precision and stability compared with 24 h resolution results, but still in the acceptable range. Both the results of 24 h resolution and high frequency series have different degrees of systematic deviation. The research above can provide a reference for calculating ERP using BeiDou observations.

Keywords

Earth rotation parameter GPS High frequency Precision analysis 

References

  1. 1.
    Wei E, Yan W, Jin S et al (2013) Improvement of Earth orientation parameters estimate with Chang’E-1 ΔVLBI observations. J Geodyn 72:46–52CrossRefGoogle Scholar
  2. 2.
    Wei E, Jin S, Zhang Q et al (2013) Autonomous navigation of Mars probe using X-ray pulsars: modeling and results. Adv Space Res 51(5):849–857CrossRefGoogle Scholar
  3. 3.
    Panafidina N, Hugentobler U, Seitz M (2015) Interaction between subdaily Earth rotation parameters and GPS orbits. Egu Gen Assembly 15.Google Scholar
  4. 4.
    Li Z, Wei E, et al (2010) Space Geodesy Google Scholar
  5. 5.
    Rothacher M et al (2001) High-frequency variations in Earth rotation from global positioning system data. J Geophys Res: Solid Earth (1978–2012) 106.B7:13711–13738Google Scholar
  6. 6.
    Zhu S, Zhao M (1986) A simplified algorithm for the joint solution of multi-techniques of ERP. Ann Shanghai Observatory Acad Sin 8Google Scholar
  7. 7.
    Wei E (2013) On the high-frequency ERPs with GPS observations. Wuhan Daxue Xuebao 38(7):818–821Google Scholar
  8. 8.
    Xu GC (2007) GPS: theory, algorithms, and applications. Springer Verlag Berlin HeidelbergGoogle Scholar
  9. 9.
    Dach R, Hugentobler U, Fridez P, Meindl M (2007) Bernese GPS software version 5.0. Astronomical Institute, University of Bern, p 640Google Scholar
  10. 10.
    Yang ZHK, Yang XH, Li ZHG et al (2010) Estimation of Earth rotation parameters by GPS observations. J Time Freq 33(001):69–76 (Chinese)Google Scholar
  11. 11.
    Wang Q, Dang Y, Xu T (2013) The method of Earth rotation parameter determination using GNSS observations and precision analysis. China Satellite Navigation Conference (CSNC) 2013 Proceedings. Springer Berlin Heidelberg, pp 247–256Google Scholar
  12. 12.
    Wei E, Wan L, Jin S et al (2014) Estimation of ERP with combined observations of GNSS and SLR. Geomatics Inform Sci Wuhan Univ 39(5):581–585Google Scholar
  13. 13.
    Herring TA, Dong D (1994) Measurement of diurnal and semidiurnal rotational variations and tidal parameters of Earth. J Geophys Res: Solid Earth (1978–2012) 99.B9:18051–18071Google Scholar
  14. 14.
    Haas Rüdiger, Wünsch Johann (2006) Sub-diurnal earth rotation variations from the VLBI CONT02 campaign. J Geodyn 41(1):94–99CrossRefGoogle Scholar
  15. 15.
    Bizouard C, Gambis D (2009) The combined solution C04 for Earth orientation parameters consistent with international terrestrial reference frame 2005. Geodetic reference frames. Springer Berlin Heidelberg, pp 265–270 Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.School of Geodesy and GeomaticsWuhan UniversityWuhanChina
  2. 2.Key Laboratory of Geospace Environment and Geodesy, Ministry of EducationWuhanChina

Personalised recommendations