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Prediction of UT1-UTC Based on Combination of Weighted Least-Squares and Multivariate Autoregressive

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China Satellite Navigation Conference (CSNC) 2013 Proceedings

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 245))

Abstract

High accurate prediction of UT1-UTC is very important for high-precision aircraft navigation and positioning. In this paper, the weighted least-squares (WLS) combined with multivariate autoregressive (MAR) is proposed to predict UT1-UTC with different span. The new method can efficiently consider the influence of time-varying for the cycle and trend terms of UT1-UTC, which is closely related to atmospheric angular momentum (AAM). The numerical example shows that the prediction accuracy of WLS + MAR method is better than that of LS + MAR method as well as LS + AR method. The results prove that the WLS + MAR model can effectively improve the prediction accuracy of UT1-UTC.

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References

  1. Zheng DW, Yu NH (1996) Earth rotation and it’s relations to geophysical phenomena: the changes of length of the day. Adv Geophys 11(2):81–101 (In Chinese)

    Google Scholar 

  2. Kosek W et al. (2004) Comparison of polar motion prediction results supplied by the IERS sub-bureau for rapid service and predictions and results of other prediction methods [A]. Astronomy Russian Academy Sciences

    Google Scholar 

  3. McCarthy DD, Luzum BJ (1991) Prediction of Earth orientation. J Geodesy, 65:18–21

    Google Scholar 

  4. Kosek W, Kalarus M, Niedzielski T (2008) Forecasting of the Earth orientation parameters—comparison of different algorithms. In: Capitaine N (ed) Proceedings of the journèes 2007, systèmes de référence spatio-temporels The celestial reference frame for the future. Observatoire de Paris Systèmes de Référence Temps-Espace UMR8630/CNRS, Paris, France, pp 155–158

    Google Scholar 

  5. Kosek W (2010a) Future improvements in EOP prediction. In: Proceedings of the IAG 2009, Geodesy for planet earth, August 31–September 4, 2009, Buenos Aires, Argentina

    Google Scholar 

  6. Xu XQ, Zhou YH (2010) High precision prediction method of earth orientation. Parameters 29(2):70–76 (In Chinese)

    Google Scholar 

  7. Kosek W, McCarthy DD, Luzum BJ (1998) Possible improvement of Earth orientation forecast using autocovariance prediction procedures. J Geodesy 72:189–199

    Article  Google Scholar 

  8. Schuh H, Ulrich M, Egger D et al (2002) Prediction of Earth orientation parameters by artificial neural networks. J Geodesy 76:247–258

    Article  Google Scholar 

  9. Wang QJ (2007) Studies on the prediction of Earth’s variable rotation by artificial neural networks [D]. Shanghai Astronomical observatory, Chinese Academy of Sciences. Shanghai, China (In Chinese)

    Google Scholar 

  10. Niedzielski T, Kosek W (2008) Prediction of UT1-UTC,LOD and AAM \( \chi_{3} \)by combination of least-squares and multivariate stochastic methods. J Geodesy, 82:83–92

    Google Scholar 

  11. Kosek W, McCarthy DD, Luzum BJ (2010) Studia geoph. Et geod 45:347

    Google Scholar 

  12. Zhang H, Wang Qj, Zhu JJ et al. (2011) Joint model of weighted least-squares and AR in prediction of polar motion 29(3):343–352 (In Chinese)

    Google Scholar 

  13. McCarthy DD, Petit G (2003) IERS conventions (2003) [S]. America

    Google Scholar 

  14. Sun ZZ, Xu TH(2012) Prediction of Earth rotation parameters based on an improved weighted least-squares and AR model. Geodesy and Geodynamics, 3(3):57–64

    Google Scholar 

Download references

Acknowledgments

This work was supported by the Foundation for the Author of National Excellent Doctoral Dissertation of China (2007B51), the Open Foundation of State Key Laboratory of Geodesy and Earth's Dynamics (SKLGED2013-4-2-EZ) and Natural Science Foundation of China (41174008).

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Authors and Affiliations

  1. School of Geology Engineering and Surveying, Chang’an University, Xi’an, Shanxi, China

    Zhang-zhen Sun

  2. State Key Laboratory of Geo-information Engineering, Xi’an, Shanxi, China

    Tian-he Xu

  3. Xian Research Institute of Surveying and Mapping, Xi’an, Shanxi, China

    Tian-he Xu

  4. State Key Laboratory of Geodesy and Earth’s Dynamics, Wuhan, China

    Tian-he Xu

Authors
  1. Zhang-zhen Sun
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  2. Tian-he Xu
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Corresponding author

Correspondence to Zhang-zhen Sun .

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Editors and Affiliations

  1. , China Aerospace Sci. & Technology Corp., Chinese Academy of Sciences, Beijing, China, People's Republic

    Jiadong Sun

  2. China Satellite Navigation Office, Beijing, China, People's Republic

    Wenhai Jiao

  3. Chinese Academy of Sciences, Dengzhuang South Road, Beijing, 100094, China, People's Republic

    Haitao Wu

  4. Wuhan University, Wuhan, China, People's Republic

    Chuang Shi

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Sun, Zz., Xu, Th. (2013). Prediction of UT1-UTC Based on Combination of Weighted Least-Squares and Multivariate Autoregressive. In: Sun, J., Jiao, W., Wu, H., Shi, C. (eds) China Satellite Navigation Conference (CSNC) 2013 Proceedings. Lecture Notes in Electrical Engineering, vol 245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37407-4_21

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  • DOI: https://doi.org/10.1007/978-3-642-37407-4_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37406-7

  • Online ISBN: 978-3-642-37407-4

  • eBook Packages: EngineeringEngineering (R0)

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