Advertisement

INS-Aided Single-Frequency Cycle-Slip Detection for Real-Time Kinematic GNSS

  • Lingxuan Wang
  • Yu Gan
  • Erhu Wei
  • Lifen Sui
  • Xuexi Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 499)

Abstract

GNSS ambiguity fixed solution can greatly improve the accuracy of GNSS/INS integrated system. But it is difficult to achieve perfect real-time dynamic single frequency cycle-slip detection merely by GNSS observations especially in complex environment. Inertial assisted cycle-slip detection terms (DTs) based on station-satellite double-differences and satellite single-difference observations are derived. The error characteristic of the DT is analyzed emphatically. The DT error is affected by the drift of INS error. In addition, the magnitude of the influence on different satellites is related to the angle between its station-satellite vector and that that vector of the reference satellite. Thus, it is important to select reference satellite. It is proposed that two group of DTs can be used together by selecting two different reference satellites. The threshold of detection is estimated in a sliding window, where the DTs, whose INS error is submerged in GNSS error, are removed in order to reflect INS error. The method of threshold estimating has stronger self-adaptability.

Keywords

GNSS/INS Cycle-slip Single frequency Reference satellite Sliding window Azimuth 

Notes

Acknowledgements

This study is supported by Nation Science Foundation of China (41374012; 41674016; 41274016) and Innovate Foundation of Information Engineering University (XS201504).

References

  1. 1.
    Li Z, Huang J (2005) GPS surveying and data processing. Wuhan University Press, WuhanGoogle Scholar
  2. 2.
    Liu J (2008) The principle and method of navigation and positioning using GPS satellites, 2nd edn. Science Press, BeijingGoogle Scholar
  3. 3.
    Li Z, Zhang X (2009) New techniques and precise data processing methods of satellite navigation and positioning. Wuhan University Press, WuhanGoogle Scholar
  4. 4.
    Yuan H, Wan W, Ning B, Li J (1998) A new cycle slip detection and correction method using triple differences solution. Acta Geod Et Cartogr Sin 27(3):189–194Google Scholar
  5. 5.
    Blewitt G (1990) An automatic editing algorithm for GPS data. Geophys Res Lett 17(3):199–202CrossRefGoogle Scholar
  6. 6.
    Fang R, Shi C, Wei N (2009) Real-time cycle-slip detection for quality control of GPS measurements. Geomat Inf Sci Wuhan Univ 34(9):1094–1097Google Scholar
  7. 7.
    Li J, Yang Y, Xu J, He H, Guo H (2011) Real-time cycle-slip detection and repair based on code-phase combinations for GNSS triple-frequency un-differenced observations. Acta Geod Et Cartogr Sin 40(6):716–717Google Scholar
  8. 8.
    Chen P (2010) Cycle slips detecting and repairing by use of phase reduce pseudorange law and ionized layer remnant method of difference. J Geod Geodyn 30(2):120–124 (Qingdao)Google Scholar
  9. 9.
    Tang Z (2011) Investigations on cycle slip detection and correction in GPS precise point positioning. Shandong University of Science and Technology, QingdaoGoogle Scholar
  10. 10.
    Altmayer C (2002) Enhancing the integrity of integrated GPS/INS systems by cycle slip detection and correction. In: Intelligent vehicles symposium. IV 2000. Proceedings of the IEEE. IEEE, pp 174–179Google Scholar
  11. 11.
    Lee HK, Wang J, Park WY, Rizos C (2003) Carrier phase processing issues for high accuracy integrated GPS/Pseudolite/INS systems. In: Proceedings of 11th IAIN World Congress, pp 252–273Google Scholar
  12. 12.
    Colombo OL, Bhapkar UV (1999) Inertial-aided cycle-slip detection/correction for precise, long-baseline kinematic GPS. In: ION GPS 1999, Nashville, USAGoogle Scholar
  13. 13.
    Du S, Gao Y (2012) Inertial aided cycle slip detection and identification for integrated PPP GPS and INS. Sensors 12(11):14344–14362CrossRefGoogle Scholar
  14. 14.
    Du S (2011) An inertial aided cycle slip detection and identification method for integrated PPP GPS/ MEMS IMU system. In: Proceedings of International Technical Meeting of the Satellite Division of the Institute of Navigation, vol 28, no 2, pp 3183–3191Google Scholar
  15. 15.
    Liu S, Sun F, Zhang L et al (2015) Instantaneous re-convergence of precise point positioning by using INS-aided cycle-slip correction. J Chin Inert Technol 23(5):607–614Google Scholar
  16. 16.
    Gan Y (2015) GNSS/INS integrated system model refining and position/attitude determination using carrier phase. Information Engineering University, Zhengzhou, pp 101–115Google Scholar
  17. 17.
    Liu Q, Sui L, Xiao G et al (2015) A method of determining the weight matrix for BDS DCB resolution. J Geomat Sci Technol 32(5):473–478Google Scholar
  18. 18.
    Zhang X, Guo F, Li P et al (2012) Real-time quality control procedure for GNSS precise point positioning. Geomat Inf Sci Wuhan Univ 37(8):940–944Google Scholar
  19. 19.
    Ma G, Yu B, Jia R et al (2016) INS-aided high dynamic GNSS rapid acquisition and stable tracking. Radio Eng 46(2):23–26Google Scholar
  20. 20.
    Ye P (2011) MEMS IMU/GNSS ultra-tight integration navigation technology. Shanghai Jiao Tong University, Shanghai, pp 15–39Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Lingxuan Wang
    • 1
  • Yu Gan
    • 2
  • Erhu Wei
    • 1
  • Lifen Sui
    • 2
  • Xuexi Liu
    • 1
  1. 1.School of Geodesy and GeomaticsWuhan UniversityWuhanChina
  2. 2.Information Engineering UniversityZhengzhouChina

Personalised recommendations