Journal of Geodesy

, Volume 91, Issue 3, pp 329–340 | Cite as

A review on the inter-frequency biases of GLONASS carrier-phase data

Original Article

Abstract

GLONASS ambiguity resolution (AR) between inhomogeneous stations requires correction of inter-frequency phase biases (IFPBs) (a “station” here is an integral ensemble of a receiver, an antenna, firmware, etc.). It has been elucidated that IFPBs as a linear function of channel numbers are not physical in nature, but actually originate in differential code-phase biases (DCPBs). Although IFPBs have been prevalently recognized, an unanswered question is whether IFPBs and DCPBs are equivalent in enabling GLONASS AR. Besides, general strategies for the DCPB estimation across a large network of heterogeneous stations are still under investigation within the GNSS community, such as whether one DCPB per receiver type (rather than individual stations) suffices, as tentatively suggested by the IGS (International GNSS Service), and what accuracy we are able to and ought to achieve for DCPB products. In this study, we review the concept of DCPBs and point out that IFPBs are only approximate derivations from DCPBs, and are potentially problematic if carrier-phase hardware biases differ by up to several millimeters across frequency channels. We further stress the station and observable specific properties of DCPBs which cannot be thoughtlessly ignored as conducted conventionally. With 212 days of data from 200 European stations, we estimated DCPBs per stations by resolving ionosphere-free ambiguities of \(\sim \)5.3 cm wavelengths, and compared them to the presumed truth benchmarks computed directly with L1 and L2 data on ultra-short baselines. On average, the accuracy of our DCPB products is around 0.7 ns in RMS. According to this uncertainty estimates, we could unambiguously confirm that DCPBs can typically differ substantially by up to 30 ns among receivers of identical types and over 10 ns across different observables. In contrast, a DCPB error of more than 6 ns will decrease the fixing rate of ionosphere-free ambiguities by over 20 %, due to their smallest frequency spacing and highest sensitivity to DCPB errors. Therefore, we suggest that (1) the rigorous DCPB model should be implemented instead of the classic, but inaccurate IFPB model; (2) DCPBs of sub-ns accuracy can be achieved over a large network by efficiently resolving ionosphere-free ambiguities; (3) DCPBs should be estimated and applied on account of their station and observable specific properties, especially for ambiguities of short wavelengths.

Keywords

GLONASS Ambiguity resolution Inter-frequency phase bias Differential code-phase bias 

References

  1. Al-Shaery A, Zhang S, Rizos C (2013) An enhanced calibration method of GLONASS inter-channel bias for GNSS RTK. GPS Solut 17(2):165–173CrossRefGoogle Scholar
  2. Banville S (2016) GLONASS ionosphere-free ambiguity resolution for precise point positioning. J Geod 90(5):487–496CrossRefGoogle Scholar
  3. Banville S, Collins P, Lahaye F (2013) GLONASS ambiguity resolution of mixed receiver types without external calibration. GPS Solut 17(3):275–282CrossRefGoogle Scholar
  4. Dai L (2000) Dual-frequency GPS/GLONASS real-time ambiguity resolution for medium-range kinematic positioning. In: Proceedings of ION GPS 13th international technical meeting of the satellite division. Salt Lake City, UT, pp 1071–1080Google Scholar
  5. Defraigne P, Sleewaegen JM, Matsakis D (2015) How important is it to synchronize the code and phase measurements of a GNSS receiver. Inside GNSS 10(6):26–32Google Scholar
  6. Dong D, Bock Y (1989) Global positioning system network analysis with phase ambiguity resolution applied to crustal deformation studies in California. J Geophys Res 94(B4):3949–3966CrossRefGoogle Scholar
  7. Ge M, Gendt G, Dick G, Zhang FP, Rothacher M (2006) A new data processing strategy for huge GNSS global networks. J Geod 80(4):199–203CrossRefGoogle Scholar
  8. Geng J, Bock Y (2016) GLONASS fractional-cycle bias estimation across inhomogeneous receivers for PPP ambiguity resolution. J Geod 90(4):379–396CrossRefGoogle Scholar
  9. Geng J, Li X (2016) Undifferenced GLONASS ambiguity resolution over inhomogeneous stations: introducing ionosphere corrections or resolving ionosphere-free ambiguities? In: Proceedings of ION GNSS+ 29th international technical meeting of the satellite division, Portland, ORGoogle Scholar
  10. IGS, RTCM (2015) RINEX: the receiver independent exchange format. Version 3:03Google Scholar
  11. Leick A (1998) GLONASS satellite surveying. J Surv Eng ASCE 124(2):91–99CrossRefGoogle Scholar
  12. Liu Y, Ge M, Shi C, Lou Y, Wickert J, Schuh H (2016) Improving integer ambiguity resolution for GLONASS precise orbit determination. J Geod. doi:10.1007/s00190-016-0904-y Google Scholar
  13. Pratt M, Burke B, Misra P (1998) Single-epoch integer ambiguity resolution with GPS-GLONASS L1–L2 data. In: Proceedings of the 11th international technical meeting of the satellite division. Nashville, TN, pp 389–398Google Scholar
  14. Schaer S (2014) Biases relevant to GPS and GLONASS data processing. In: IGS Workshop 2014, Pasadena, CA, USA, 23–27 JunGoogle Scholar
  15. Schaer S (2016) SINEX-Bias-Solution independent exchange format for GNSS biases version 1.00 (draft). In: IGS Workshop on GNSS biases, Bern, Switzerland, 5–6 NovGoogle Scholar
  16. Sleewaegen JM, Simsky A, De Wilde W, Boon F, Willems T (2012) Demystifying GLONASS inter-frequency carrier phase biases. Inside GNSS 7(3):57–61Google Scholar
  17. Takac F (2009) GLONASS inter-frequency biases and ambiguity resolution. Inside GNSS 4(2):24–28Google Scholar
  18. Takac F, Alves P (2012) GLONASS RTK interoperability issues involving 3rd party receivers. In: IGS Workshop on GNSS Biases, Bern, Switzerland, 18–19 JanGoogle Scholar
  19. Tian Y, Ge M, Neitzel F (2015) Particle filter-based estimation of inter-frequency phase bias for real-time GLONASS integer ambiguity resolution. J Geod 89(13):1145–1158CrossRefGoogle Scholar
  20. Wang J (2000) An approach to GLONASS ambiguity resolution. J Geod 74(5):421–430CrossRefGoogle Scholar
  21. Wanninger L (2012) Carrier-phase inter-frequency biases of GLONASS receivers. J Geod 86(2):138–148CrossRefGoogle Scholar
  22. Wanninger L, Wallstab-Freitag S (2007) Combined processing of GPS, GLONASS, and SBAS code phase and carrier phase measurements. In: Proceedings of ION GNSS 20th international technical meeting of the satellite division. Fort Worth, TX, pp 866–875Google Scholar
  23. Zyryanov G (2012) GLONASS phaserange biases in RTK processing. In: IGS Workshop on GNSS Biases, Bern, Switzerland, 18–19 JanGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Jianghui Geng
    • 1
    • 2
  • Qile Zhao
    • 1
    • 2
  • Chuang Shi
    • 1
    • 2
  • Jingnan Liu
    • 1
    • 2
  1. 1.GNSS Research CenterWuhan UniversityWuhanChina
  2. 2.Collaborative Innovation Center of Earth and Space ScienceWuhan UniversityWuhanChina

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