Abstract
With the development of Global Navigation Satellite Systems, different types of signals and sensors, such as pilot and data signals and inertial measurement unit observations, will be fused in one tracking loop to achieve better performance. The update-rates of those measurements may be different. This issue cannot be dealt by the conventional dual update-rate phase locked loop (DUPLL) technique. To solve this problem, a generalized model called multiple update-rate Kalman filter (MUKF) is explored; it can fuse multiple update-rates measurements in one tracking loop. To improve the robustness of MUKF in challenging environments such as indoors, a robust MUKF (RMUKF) based on an adaptive factor of a three-segment function is designed. The adaptive factor can adjust the contribution of different measurements on the fusion loop automatically and improve the robustness performance. Simulation and experimental results show that the RMUKF has better performance than the DUPLL in terms of robustness and sensitivity.
Similar content being viewed by others
References
Borio D, Anantharamu P, Lachapelle G (2011) SATLSim: a semi-analytic framework for fast GNSS tracking loop simulations. GPS Solut 15(4):427–431
Brown R, Hwang P (2012) Intermediate topics on Kalman filtering. Introduction to random signals and applied Kalman filtering, Chapter 5. Wiley, New York
IS-GPS-705-A (2010) Global positioning system wing systems engineering & Integration interface specification IS-GPS-705, Rev A. Navstar GPS Space Segment/User Segment L5 Interfaces
Jiang R, Wang K, Liu S, Li Y (2017) Performance analysis of a Kalman filter carrier phase tracking loop. GPS Solut 21(2):551–559
Jin L, Yao Z, Cui X, Lu M, Feng Z (2011) Dual update-rate FLL-assisted phase lock loop of novel robust receivers for new generation global navigation satellite signals. In: Proceedings ION ITM 2011, institute of navigation, Portland OR, USA, September 19–23, 3652–3659
Jovanovic A, Mongredien C, Tawk Y, Botteron C, Farine P, Rohmer G (2011) Implementation and optimization of a Galileo E1 Two-Step tracking algorithm using data/pilot combining and extended integration time. In: Proceedings ION ITM 2011, institute of navigation, Portland OR, USA, September 19–23, 3756–3766
Kaplan ED, Hegarty CJ (2006) Understanding GPS: principles and applications, 2nd edn. Artech House Publishers, Norwood, pp 134–141
Lv P, Lu M, Yao Z (2013) Dual update-rate INS aided carrier phase lock loop for new generation global navigation satellite signals. In: Proceedings CSNC 2013, China satellite navigation conference, Wuhan, China, May 15–17, 715–724
Muthuraman K, Klukas R, Lachapelle G (2008) Performance evaluation of L2C data/pilot combined carrier tracking. Proceedings ION GNSS 2008, institute of navigation, Savannah, Georgia, USA, September 16–19, 1658–1666
Muthuraman K, Borio D, Klukas R, Lachapelle G (2010) Adaptive data pilot carrier phase tracking for modernized GNSS signals. In: Proceedings ION ITM 2010, institute of navigation, San Diego, CA, USA, January 25–27,736–749
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):345–356
OS SIS ICD (2010) European GNSS (Galileo) open service signal in space interface control document. Issue 1
Parkinson BW and Spilker JJ (1996) Global position system: theory and applications. Am Instit Aeronaut Astronaut, 485–515
Psiaki M.L and Jung H (2002) Extended Kalman filter method for tracking weak GPS signals. In: Proceedings ION GPS 2002, Institute of Navigation, Portland, OR, USA, September 24–27, 2539–2553
Salem D, O’Driscoll C, Lachapelle G (2012) Methodology for comparing two carrier phase tracking techniques. GPS Solut 16(2):197–207
Shen Y, Zhang L, Fu Z, Wang J (2012) The research on the combination of discriminators in Galileo L1F signal carrier tracking loop. J Astronaut 33(3):380–386 (in Chinese)
Tan S, Zhou B, Guo S, Liu Z (2011) Research on COMPASS Navigation Signals of China. Chin Space Sci Technol 31(4):9–14 (in Chinese)
Wang J, Ni S, Tang X, Ou G (2012) Tracking threshold analysis of a kind of FLL based on Kalman filter. In: Proceedings ITSE 2012, international conference on information technology and software engineering, Beijing, China, December 8–10, 527–534. https://doi.org/10.1007/978-3-642-34528-9_54
Yang Y, Gao W (2005) Comparison of adaptive factors in Kalman filters on navigation results. The J Navig 58:471–478. https://doi.org/10.10007/S0373463305003292
Yao Z, Cui X, Lu M, Feng Z (2009) Dual update-rate carrier tracking technique for new generation global navigation satellite system signals in dynamic environments. IET Radar Sonar Navig 3(3):203–213
Acknowledgements
The authors thank Chunjiang Ma for the help of the real data collected, thank Prof. Leick and anonymous reviewers for their valuable comments which significantly improved the quality of this paper.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lin, H., Huang, Y., Tang, X. et al. Robust multiple update-rate Kalman filter for new generation navigation signals carrier tracking. GPS Solut 22, 10 (2018). https://doi.org/10.1007/s10291-017-0679-5
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10291-017-0679-5