GPS Solutions

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Improved prediction of GPS satellite clock sub-daily variations based on daily repeat

Original Article
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Abstract

High-precision estimates of GPS satellite clock errors reveal systematic sub-daily clock bias variations on the order of 1 ns. The low noise levels in the Rubidium Atomic Frequency Standards onboard GPS IIR, IIR-M, and IIF satellites provide visibility of these small, but systematic behaviors. Prior studies have reported on this phenomenon and sought to characterize the specific frequency components present and to identify potential causes of the observed periodic variations. Our research focuses on the repeatability of the clock variations and the potential for using observed variations directly to predict future clock behavior. Results are presented and compared to IGS Ultra-rapid and broadcast message predictions for all operating GPS satellite clocks for a 1-month period in July 2017. During this time, the accuracy of the proposed sub-daily variation prediction is better than 0.15 ns (RMS) for 8 out of 9 GPS Block IIF Rb clocks and under 0.3 ns (RMS) for most GPS IIR and IIR-M Rb clocks. This approach is complementary to existing techniques for estimating longer-term clock rates and drift and can be combined with them to improve the fidelity of predictive satellite clock models for real-time GPS position, navigation, and timing applications.

Keywords

GPS satellite clocks Rubidium clock Allan variance Repeatability 

Notes

Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments and recommendations and Dr. Ben Bradley and Dr. John Pratt for their MATLAB codes used in support of this work.

References

  1. Axelrad P, Larson KM, Jones B (2005) Use of the correct satellite repeat period to characterize and reduce site specific multipath errors. In: Proceedings of ION GNSS-2005, Long Beach, CA, pp 2638–2648Google Scholar
  2. Beard R, White J, Brad J, Myers T, Reid W, Danzy F, Buisson J (2000) Long term ground test results for two GPS Block IIR rubidium clocks. In: Proceedings of ION NTM 2000, Anaheim, CA, pp 381–387Google Scholar
  3. Choi K, Bilich A, Larson KM, Axelrad P (2004) Modified sidereal filtering: implications for high-rate GPS positioning. Geophys Res Lett 31:L22608.  https://doi.org/10.1029/2004GL021621 CrossRefGoogle Scholar
  4. Davis J, Bhattarai S, Ziebart M (2012) Development of a Kalman filter based GPS satellite clock time-offset prediction algorithm. Eur Freq Time Forum (EFTF).  https://doi.org/10.1109/EFTF.2012.6502355 Google Scholar
  5. Dow JM, Neilan RE, Rizos C (2009) The international GNSS service in a changing landscape of global navigation satellite systems. J Geodesy 83:191–198.  https://doi.org/10.1007/s00190-008-0300-3 CrossRefGoogle Scholar
  6. Dupuis RT, Lynch TJ, Vaccaro JR, Watts ET (2010) Rubidium frequency standard for the GPS IIF program and modifications for the RAFSMOD program. In: Proceedings of ION GNSS + 2010, Portland, OR, pp 781–788Google Scholar
  7. Epstein M, Dass T (2001) Management of phase and frequency for GPS IIR satellites. In: Proceedings of the 33th annual precise time and time interval systems and applications meeting, Long Beach, California, pp 481–492Google Scholar
  8. GPS (2008) Global positioning system standard positioning service performance standard, 4th edn, September 2008Google Scholar
  9. Huang GW, Zhang Q, Xu GC (2014) Real-time clock offset prediction with an improved model. GPS Solut 18(1):95–104CrossRefGoogle Scholar
  10. IGS (2014) Real-time service fact sheet. http://rts.igs.org/monitor/
  11. Montenbruck O, Hugentobler U, Dach R, Steigenberger P, Hauschild A (2012a) Apparent clock variations of the Block IIF-1 (SVN62) GPS satellite. GPS Solut 16(3):303–313CrossRefGoogle Scholar
  12. Montenbruck O, Steigenberger P, Schönemann E, Hauschild A, Hugentobler U, Dach R, Becker M (2012b) Flight characterization of new generation GNSS satellite clocks. Navigation 59(4):291–302CrossRefGoogle Scholar
  13. Parkinson BW, Enge PK (1996) Differential GPS. In: Parkinson BW, Spilker JJ (eds) Global positioning system: theory and applications, vol II. AIAA, Reston, VACrossRefGoogle Scholar
  14. Riley WR (2008) Handbook of frequency stability analysis. NIST special publication 1065 National Institute of Standards and Technology, Boulder, COGoogle Scholar
  15. Senior KL, Coleman MJ (2017) The next generation GPS time. Navigation 64(4):411–426CrossRefGoogle Scholar
  16. Senior K, Ray JR, Beard RL (2008) Characterization of periodic variations in the GPS satellite clocks. GPS Solut 12(3):211–225.  https://doi.org/10.1007/s10291-008-0089-9 CrossRefGoogle Scholar
  17. van Diggelen F (2009) A-GPS, assisted GPS, GNSS, and SBAS. Artech House, Boston, MAGoogle Scholar
  18. Vannicola F, Beard R, White J, Senior K, Kubik K, Wilson D (2010) GPS block IIF rubidium frequency standard life test. In: Proceedings of the 23rd international technical meeting of the satellite division of the ION GNSS + 2010, Portland, OR, pp 812–819Google Scholar
  19. Wang YP, Lu ZP, Qu YY, Li LY, Wang N (2017) Improving prediction performance of GPS satellite clock bias based on wavelet neural network. GPS Solut 21:523–534CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Colorado Center for Astrodynamics Research, Ann and H.J. Smead Aerospace Engineering SciencesUniversity of Colorado BoulderBoulderUSA

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