Advertisement

Journal of Geodesy

, Volume 93, Issue 10, pp 2037–2051 | Cite as

Multipath extraction and mitigation for high-rate multi-GNSS precise point positioning

  • Kai Zheng
  • Xiaohong Zhang
  • Pan LiEmail author
  • Xingxing Li
  • Maorong Ge
  • Fei Guo
  • Jizhang Sang
  • Harald Schuh
Original Article
  • 225 Downloads

Abstract

Multipath effect on carrier-phase observation is one of the bottlenecks for mm-level applications when using precise point positioning (PPP). Hence, we extract the multipath directly from raw carrier-phase residuals of GPS, GLONASS, Galileo, and BDS, by using PPP technique. Although the residuals for one frequency assimilate the errors from other frequencies, which is caused by error adjustment by the least squares estimator, the primary component of residuals is multipath. The results indicate that the residuals between frequencies have a significant linear negative correlation and synchronous time lag for each system. Besides BDS Geostationary Earth Orbit satellites, the residuals for other satellites can establish accurate mathematic relationship between the frequencies. For GLONASS, the residuals of R1 frequency recovered from R2 frequency with the mathematical relationship are better than 0.1 mm accuracy, which means the effect of inter-frequency bias can be neglected. These regularities double-reduce the complexity of data processing. Based on the multipath distribution, we propose a modified Multipath Hemispherical Map model (M-MHM), which constructs grids from residuals and is divided into three equal-elevation angle parts with an optimal resolution 0.2° × 0.2° × 1° from numerous experiments. In addition, the multipath manifests great consistency among satellites for GPS, GLONASS, and Galileo systems when elevation angles are higher than 15°, while is more satellite dependent for BDS. Although GPS L1 frequency is identical to Galileo E1, the model still has some systematic bias between GPS and Galileo. Compared with sidereal filtering and original MHM model, the M-MHM brings the highest improvement in both residual variance reduction and positioning accuracy. The positioning accuracy is on average 12% improvement compared to MHM and 29% improvement compared to SF. For four systems combined solutions with the M-MHM model, can reach an accuracy of 0.75, 0.55, and 2.08 cm in the east, north, and up components.

Keywords

Multipath model Multi-GNSS PPP Raw carrier-phase observation 

Notes

Acknowledgements

We gratefully acknowledge financial support from China Scholarship Council (CSC, file 201706270123). This work is funded by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 41721003), and The National Key Research and Development Program of China (Nos. 2016YFB0501803, 2017YFB0503402).

Author contributions

KZ conceived and designed the research and analyzed the data; KZ and PL performed the research; KZ wrote the paper; XZ and MG provided advice. The paper was modified by XZ, PL, XL, MG, FG, JS, and HS.

References

  1. Agnew DC, Larson KM (2007) Finding the repeat times of the GPS constellation. GPS Solut 11(1):71–76.  https://doi.org/10.1007/s10291-006-0038-4 CrossRefGoogle Scholar
  2. Atkins C, Ziebart M (2016) Effectiveness of observation-domain sidereal filtering for GPS precise point positioning. GPS Solut 20(1):111–122.  https://doi.org/10.1007/s10291-015-0473-1 CrossRefGoogle Scholar
  3. Axelrad P, Comp C, Macdoran P (1996) SNR-based multipath error correction for GPS differential phase. IEEE Trans Aerosp Electron Syst 32(2):650–660.  https://doi.org/10.1109/7.489508 CrossRefGoogle Scholar
  4. Bender M, Dick G, Wickert J, Schmidt T, Song S, Gendt G, Ge M, Rothacher M (2008) Validation of GPS slant delays using water vapour radiometers and weather models. Meteorol Z 17(6):807–812.  https://doi.org/10.1127/0941-2948/2008/0341 CrossRefGoogle Scholar
  5. Bilich A, Larson KM (2007) Mapping the GPS multipath environment using the signal-to-noise ratio (SNR). Radio Sci 42(6):RS6003.  https://doi.org/10.1029/2007RS003652 CrossRefGoogle Scholar
  6. Boehm J, Niell A, Tregoning P, Schuh H (2006) Global Mapping Function (GMF): a new empirical mapping function based on numerical weather model data. Geophys Res Lett 33(7):L07304.  https://doi.org/10.1029/2005GL025546 CrossRefGoogle Scholar
  7. Braasch MS (1996) Multipath effects. In: Parkinson BW et al (eds) Global positioning system: theory and applications, vol 1. AIAA Press, Washington, DCGoogle Scholar
  8. China Satellite Navigation Office (CSNO) (2019) BeiDou navigation satellite system signal in space interface control document. http://www.beidou.gov.cn/xt/gfxz/201902/P020190227593621142475.pdf. Accessed 15 Sept 2019
  9. Choi K, Bilich A, Larson K, Axelrad P (2004) Modified sidereal filtering: implications for high-rate GPS positioning. Geophys Res Lett 31(22):L22608.  https://doi.org/10.1029/2004GL021621 CrossRefGoogle Scholar
  10. Coster AJ, Goncharenko L, Zhang SR, Erickson PJ, Rideout W, Vierinen J (2017) GNSS observations of ionospheric variations during the 21 August 2017 solar eclipse. Geophys Res Lett 44(24):12041–12048.  https://doi.org/10.1002/2017GL075774 CrossRefGoogle Scholar
  11. Deng Z, Zhao Q, Springer T, Prange L, Uhlemann M (2014) Orbit and clock determination-BeiDou. In: IGS workshop, Pasadena, USA, 23–27 June 2014Google Scholar
  12. Dong D, Wang M, Chen W, Zeng Z, Song L, Zhang Q, Cai M, Cheng Y, Lv J (2016) Mitigation of multipath effect in GNSS short baseline positioning by the multipath hemispherical map. J Geod 90(3):255–262.  https://doi.org/10.1007/s00190-015-0870-9 CrossRefGoogle Scholar
  13. European Union (2014) European GNSS (Galileo) open service signal in space interface control document. OS SIS ICD, Issue 1.2Google Scholar
  14. Fuhrmann T, Luo X, Knöpfler A, Mayer M (2015) Generating statistically robust multipath stacking maps using congruent cells. GPS Solut 19(1):83–92.  https://doi.org/10.1007/s10291-014-0367-7 CrossRefGoogle Scholar
  15. Geng J, Williams SDP, Teferle FN, Dodson AH (2012) Detecting storm surge loading deformations around the southern North Sea using subdaily GPS. Geophys J Int 19(2):569–578.  https://doi.org/10.1111/j.1365-246X.2012.05656.x CrossRefGoogle Scholar
  16. Geng J, Jiang P, Liu J (2017) Integrating GPS with GLONASS for high-rate seismogeodesy. Geophys Res Lett 44(7):3139–3146.  https://doi.org/10.1002/2017GL072808 CrossRefGoogle Scholar
  17. Geng J, Pan Y, Li X, Guo J, Liu J, Chen X, Zhang Y (2018) Noise characteristics of high-rate multi-GNSS for subdaily crustal deformation monitoring. J Geophys Res 123(2):1987–2002.  https://doi.org/10.1002/2018JB015527 CrossRefGoogle Scholar
  18. Genrich J, Bock Y (1992) Rapid resolution of crustal motion at short ranges with the global positioning system. J Geophys Res 97(B3):3261–3269.  https://doi.org/10.1029/91JB02997 CrossRefGoogle Scholar
  19. Georgiadou Y, Kleusberg A (1988) On carrier signal multipath effects in relative GPS positioning. Manuscr Geodaet 13(3):172–179Google Scholar
  20. GPS Directorate (2012) Navstar GPS space segment/navigation user segment interfaces. Interface specification IS-GPS-200, revision G, 5 September 2012, Global Positioning Systems DirectorateGoogle Scholar
  21. Han S, Rizos C (1997) Multipath effects on GPS in mine environments. In: 10th international congress for mine surveying, Fremantle, Australia, November 2–6, pp 447–457Google Scholar
  22. Hofmann-Wellenhof B, Lichtenegger H, Wasle E (2008) GNSS global navigation satellite systems: GPS, GLONASS. Galileo and more. Springer, BerlinGoogle Scholar
  23. Kouba J (2015) A guide to using international GNSS service (IGS) products. http://kb.igs.org/hc/en-us/articles/201271873-A-Guide-to-Using-the-IGS-Products. Accessed 15 Sept 2019
  24. Larson KM, Bilich A, Axelrad P (2007) Improving the precision of high-rate GPS. J Geophys Res 112:B05422.  https://doi.org/10.1029/2006JB004367 CrossRefGoogle Scholar
  25. Li X, Ge M, Dai X, Ren X, Fritsche M, Wickert J, Schuh H (2015) Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo. J Geod 89(6):607–635.  https://doi.org/10.1007/s00190-015-0802-8 CrossRefGoogle Scholar
  26. Li X, Li X, Yuan Y, Zhang K, Zhang X, Wickert J (2018a) Multi-GNSS phase delay estimation and PPP ambiguity resolution: GPS, BDS, GLONASS. Galileo. J Geod 92(6):579–608.  https://doi.org/10.1007/s00190-017-1081-3 CrossRefGoogle Scholar
  27. Li P, Zhang XH, Ge MR, Schuh H (2018b) Three-frequency BDS precise point positioning ambiguity resolution based on raw observables. J Geod 92(12):1357–1369.  https://doi.org/10.1007/s00190-018-1125-3 CrossRefGoogle Scholar
  28. Lidberg M, Eksröm C, Johansson JM (2009) Site-dependent effects in high-accuracy applications of GNSS. EUREF Publication No. 17, Mitteilungen des Bundesamtes für Kartographie und Geodäsie, Band 42, pp 132–138Google Scholar
  29. Lu CX, Li X, Li ZH, Heinkelmann R, Nilsson T, Dick G, Ge MR, Schuh H (2016) GNSS tropospheric gradients with high temporal resolution and their effect on precise positioning. J Geophys Res 121(2):912–930.  https://doi.org/10.1002/2015JD024255 CrossRefGoogle Scholar
  30. Montenbruck O, Steigenberger P, Khachikyan R, Weber G, Langley RB, Mervart L, Hugentobler U (2014) IGSMGEX: preparing the ground for multi-constellation GNSS science. Inside GNSS 9(1):42–49Google Scholar
  31. Psimoulis PA, Houlié N, Behr Y (2018) Real-time magnitude characterization of large earthquakes using the predominant period derived from 1 Hz GPS data. Geophys Res Lett 45(2):517–526.  https://doi.org/10.1002/2017GL075816 CrossRefGoogle Scholar
  32. Rost C, Wanninger L (2009) Carrier phase multipath mitigation based on GNSS signal quality measurements. J Appl Geod 3(2):81–87.  https://doi.org/10.1515/JAG.2009.009 CrossRefGoogle Scholar
  33. Snedecor GW, Cochran WG (1980) Statistical methods, 7th edn. Iowa State University Press, AmesGoogle Scholar
  34. Su M, Zheng J, Yang Y, Wu Q (2018) A new multipath mitigation method based on adaptive thresholding wavelet denoising and double reference shift strategy. GPS Solut 22(2):40.  https://doi.org/10.1007/s10291-018-0708-z CrossRefGoogle Scholar
  35. Wübbena G, Schmitz M, Matzke N (2010) On GNSS in situ-station calibration of near field multipath. In: International symposium on GNSS space based and ground based augmentation systems and applications, Brussels, BelgiumGoogle Scholar
  36. Zheng K, Zhang X, Li X, Li P, Sang J, Ma T, Schuh H (2019) Capturing coseismic displacement in real time with mixed single- and dual-frequency receivers: application to the 2018 mw7.9 Alaska earthquake. GPS Solut 23(1):9.  https://doi.org/10.1007/s10291-018-0794-y CrossRefGoogle Scholar
  37. Zhong P, Ding X, Zheng D, Chen W (2008) Adaptive wavelet transform based on cross-validation method and its application to GPS multipath mitigation. GPS Solut 12(2):109–117.  https://doi.org/10.1007/s10291-007-0071-y CrossRefGoogle Scholar
  38. Zumberge JF, Heflin MB, Jefferson DC, Watkins MM, Webb FH (1997) Precise point positioning for the efficient and robust analysis of GPS data from large networks. J Geophys Res 102(B3):5005–5017.  https://doi.org/10.1029/96JB03860 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Kai Zheng
    • 1
    • 2
  • Xiaohong Zhang
    • 1
  • Pan Li
    • 2
    Email author
  • Xingxing Li
    • 1
  • Maorong Ge
    • 2
  • Fei Guo
    • 1
  • Jizhang Sang
    • 1
  • Harald Schuh
    • 2
    • 3
  1. 1.School of Geodesy and GeomaticsWuhan UniversityWuhanChina
  2. 2.German Research Centre for Geosciences GFZPotsdamGermany
  3. 3.Technische Universität BerlinBerlinGermany

Personalised recommendations