Advertisement

GPS Solutions

, 23:15 | Cite as

Improvement of carrier phase tracking in high dynamics conditions using an adaptive joint vector tracking architecture

  • Shaohua ChenEmail author
  • Yang Gao
Original Article
  • 192 Downloads

Abstract

The standard vector phase-locked loop (VPLL) with fixed pre-defined process noise covariance matrix usually loses lock when the receiver experiences high dynamic conditions. Two adaptive Kalman filters (KF), widely used for position calculation in Global Navigation Satellite System (GNSS) receivers, and their characteristics are analyzed and considered as potential solutions to this issue. An adaptive joint VPLL is then proposed and implemented to improve phase tracking performance in high dynamic conditions. In the proposed adaptive joint VPLL, the outputs of the individual filters in the joint VPLL are used to adaptively adjust the process noise covariance matrix of the common filter based on an Extended KF (EKF). A hardware simulator test and a field test have been conducted to assess the performance of the proposed adaptive joint VPLL, which is compared with the conventional VPLL. The test results show that the adaptive joint VPLL can improve the robustness of carrier phase tracking in high dynamic conditions.

Keywords

Carrier phase tracking High dynamics GNSS Receiver 

Notes

References

  1. Brewer J, Raquet J (2016) Differential vector phase locked loop. IEEE Trans Aerosp Electron Syst 52(3):1046–1055CrossRefGoogle Scholar
  2. Chen S, Gao Y (2017) Improvement of carrier phase tracking based on a joint vector architecture. Int J Aerosp Eng.  https://doi.org/10.1155/2017/9682875 CrossRefGoogle Scholar
  3. Chen S, Gao Y, Lin T (2017) Effect and mitigation of oscillator vibration-induced phase noise on carrier phase tracking. GPS Solut 21(4):1515–1524CrossRefGoogle Scholar
  4. Curran JT (2015) Enhancing weak-signal carrier phase tracking in GNSS receivers. Int J Navig Obs.  https://doi.org/10.1155/2015/295029 CrossRefGoogle Scholar
  5. Curran J, Lachapelle G, Murphy C (2012) Digital GNSS PLL design conditioned on thermal and oscillator phase noise. IEEE Trans Aerosp Electron Syst 48(1):180–196CrossRefGoogle Scholar
  6. Falletti E, Pini M, Presti LL (2011) Low complexity carrier-to-noise ratio estimators for GNSS digital receivers. IEEE Trans Aerosp Electron Syst 47(1):420–437CrossRefGoogle Scholar
  7. Giger K (2014) Multi-signal tracking in GNSS. Ph.D. Thesis, Department of Electrical and Computer Engineering, Technical University of MunichGoogle Scholar
  8. Giger K, Henkel P, Günther C (2009) Multifrequency multisatellite carrier tracking. In: Proceedings of 4th European workshop on GNSS signals and signal processing, Oberpfaffenhofen, GermanyGoogle Scholar
  9. Henkel P, Giger K, Günther C (2009) Multifrequency, multisatellite vector phase-locked loop for robust carrier tracking. IEEE J Sel Top Signal 3(4):674–681CrossRefGoogle Scholar
  10. Jiang R, Wang K, Liu S, Li Y (2017) Performance analysis of a Kalman filter carrier phase tracking loop. GPS Solut 2(21):551–559CrossRefGoogle Scholar
  11. Martin S, Bevly D (2017) Performance analysis of a RTK vector phase locked loop architecture in degraded environments. In: Proceedings of ION PNT 2017, Institute of Navigation, Honolulu, Hawaii, USA, May 1–4, pp 383–397Google Scholar
  12. Mohamed A, Schwarz K (1999) Adaptive Kalman filtering for INS/GPS. J Geod 73(4):193–203CrossRefGoogle Scholar
  13. Niu X, Li B, Ziedan N, Guo W, Liu J (2017) Theoretical analysis and tuning criteria of the Kalman filter-based tracking loop. GPS Solut 21(1):123–135CrossRefGoogle Scholar
  14. O’Driscoll C, Petovello M, Lachapelle G (2011) Choosing the coherent integration time for Kalman filter-based carrier-phase tracking of GNSS signals. GPS Solut 15(4):345–356CrossRefGoogle Scholar
  15. Pany T, Eissfeller B (2006) Use of a vector delay lock loop receiver for GNSS signal power analysis in bad signal conditions. In: Proceedings of IEEE/ION PLANS 2006, Institute of Navigation, San Diego, California, USA, April 25–27, pp 893–903Google Scholar
  16. Petovello MG, Lachapelle G (2006) Comparison of vector-based software receiver implementations with application to ultra-tight GPS/INS integration. In: Proceedings of ION GNSS 2006, Institute of Navigation, Fort Worth, TX, September 26–29, pp 1790–1799Google Scholar
  17. Psiaki M, Jung H (2002) Extended Kalman filter methods for tracking weak GPS signals. In: Proceedings of ION GPS 2002, Institute of Navigation, Portland, Oregon, USA, September 24–27, pp 2539–2553Google Scholar
  18. Skone S, Lachapelle G, Yao D, Yu W, Watson R (2005) Investigating the impact of ionospheric scintillation using a GPS software receiver. In: Proceedings of ION GNSS 2005, Institute of Navigation, Long Beach, California, USA, September 13–16, pp 1126–1137Google Scholar
  19. Spilker JJ (1996) Fundamentals of signal tracking theory. In: Parkinson BW, Spilker JJ, Enge P (eds) Global positioning system: theory and applications, vol 1. American Institute of Aeronautics and Astronautics, Inc., Washington, DC, pp 245–327CrossRefGoogle Scholar
  20. Tang X, Falco G, Falletti E, Presti L (2015) Theoretical analysis and tuning criteria of the Kalman filter-based tracking loop. GPS Solut 19(3):489–503CrossRefGoogle Scholar
  21. Tang X, Falco G, Falletti E, Presti L (2017) Complexity reduction of the Kalman filter-based tracking loops in GNSS receivers. GPS Solut 21(2):685–699CrossRefGoogle Scholar
  22. Van Dierendonck AJ (1996) GPS receivers. In: Parkinson BW, Spilker JJ, Enge P (eds) Global positioning system: theory and applications, vol 1. American Institute of Aeronautics and Astronautics, Inc., Washington, DC, pp 329–407Google Scholar
  23. Won J, Dötterböck D, Eissfeller B (2010) Performance comparison of different forms of Kalman filter approaches for a vector-based GNSS signal tracking loop. Navigation 57(3):185–199CrossRefGoogle Scholar
  24. Won J, Pany T, Eissfeller B (2012) Characteristics of Kalman filters for GNSS signal tracking loop. IEEE Trans Aerosp Electron Syst 48(4):3671–3681CrossRefGoogle Scholar
  25. Yang R, Ling K, Poh E, Morton Y (2017a) Generalized GNSS signal carrier tracking: part I—modeling and analysis. IEEE Trans Aerosp Electron Syst 53(4):1781–1797CrossRefGoogle Scholar
  26. Yang R, Morton Y, Ling K, Poh E (2017b) Generalized GNSS signal carrier tracking: part II—optimization and implementation. IEEE Trans Aerosp Electron Syst 53(4):1798–1811CrossRefGoogle Scholar
  27. Zhang T, Niu X, Ban Y, Zhang H, Shi C, Liu J (2015) Modeling and development of INS-aided PLLs in a GNSS/INS deeply-coupled hardware prototype for dynamic applications. Sensors 15(1):733–759CrossRefGoogle Scholar
  28. Zhang T, Ban Y, Niu X, Guo W, Liu J (2017) Improving the design of MEMS INS-aided PLLs for GNSS carrier phase measurement under high dynamics. Micromachines 8(5):135.  https://doi.org/10.3390/mi8050135 CrossRefGoogle Scholar
  29. Zhao S, Akos D (2011) An open source GPS/GNSS vector tracking loop—implementation, filter tuning, and results. In: Proceedings of ION ITM 2011, Institute of Navigation, San Diego, California, USA, January 24–26, pp 1293–1305Google Scholar
  30. Zhodzishsky M, Yudanov S, Veitsel V, Ashjaee J (1998) Co-Op tracking for carrier phase. In: Proceedings of ION ITM 1998, Institute of Navigation, Nashville, TN, September 15–18, pp 653–664Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Department of Geomatics EngineeringUniversity of CalgaryCalgaryCanada

Personalised recommendations