Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-24T11:46:06.711Z Has data issue: false hasContentIssue false
  • English
  • Français

An Innovative Approach for Atmospheric Error Mitigation Using New GNSS Signals

Published online by Cambridge University Press:  14 October 2011

Lei Yang ,
Zeynep Elmas ,
Chris Hill ,
Marcio Aquino  and
Terry Moore
Lei Yang*
Affiliation:
(Institute of Engineering Surveying and Space Geodesy, University of Nottingham, Nottingham, UKNG7 2TU)
Zeynep Elmas
Affiliation:
(Institute of Engineering Surveying and Space Geodesy, University of Nottingham, Nottingham, UKNG7 2TU)
Chris Hill
Affiliation:
(Institute of Engineering Surveying and Space Geodesy, University of Nottingham, Nottingham, UKNG7 2TU)
Marcio Aquino
Affiliation:
(Institute of Engineering Surveying and Space Geodesy, University of Nottingham, Nottingham, UKNG7 2TU)
Terry Moore
Affiliation:
(Institute of Engineering Surveying and Space Geodesy, University of Nottingham, Nottingham, UKNG7 2TU)
*
(Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

New signals from the modernised satellite navigation systems (GPS and GLONASS) and the ones that are being developed (COMPASS and GALILEO) will present opportunities for more accurate and reliable positioning solutions. Successful exploitation of these new signals will also enable the development of new markets and applications for difficult environments where the current Global Navigation Satellite Systems (GNSS) cannot provide satisfying solutions. This research is aiming to exploit the improvement in monitoring, modelling and mitigating the atmospheric effects using the increased number of signals from the future satellite systems. Preliminary investigations were conducted on the numerical weather parameter based horizontal tropospheric delay modelling, as well as the ionospheric higher order and scintillation effects. Results from this research are expected to provide a potential supplement to high accuracy positioning techniques.

Keywords

New GNSS SignalsAtmospheric Error Mitigation
Type
Research Article
Information
The Journal of Navigation , Volume 64 , Supplement S1: Chinese Beidou and the Next Generation GNSS , November 2011 , pp. S211 - S232
Copyright
Copyright © The Royal Institute of Navigation 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Aquino, M., Andreotti, M., Dodson, A. and Strangeways, H. (2007). On the use of ionospheric scintillation indices as input to receiver tracking models. Advances in Space Research, 40(3), 426–435.Google Scholar
Baby, H. B., Golé, P. and Lavergnat, J. (1988). A model for the tropospheric excess path length of radio waves from surface meteorological measurements. Radio Science, 23(6), 1023–1038.CrossRefGoogle Scholar
Boehm, J. and Schuh, H. (2003). Vienna mapping functions. Proceedings of 16th Working Meeting on European VLBI for Geodesy and Astrometry, Leipzig, Germany.Google Scholar
Boehm, J., Werl, B. and Schuh, H. (2006a). Troposphere mapping functions for GPS and Very Long Baseline Interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data. Journal of Geophysical Research, 111, ARTN B02406, doi: 10.1029/2005JB003629.Google Scholar
Boehm, J., Niell, A. E., Tregoning, P. and Schuh, H. (2006b). Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model data. Geophysical Research Letters, 33, L07304, doi:10.1029/2005GL025546.Google Scholar
Cerdeira, R. P., Schubert, F., Amarillo, F., Borrel, V., Giraud, J. and Crisci, M. (2009). Ionospheric Scintillations: Simulation, Performance Verification and Analysis of Detection Algorithms on GNSS Receivers. Proceedings of 2nd International Colloquium – Scientific and Fundamental Aspects of the Galileo Program, Padua, Italy.Google Scholar
Conker, R. S., El-Arini, M. B., Hegarty, C. J. and Hsiao, T. (2003). Modeling the effects of ionospheric scintillation on GPS/SBAS availability. Radio Science, 38(1), 23, ARTN 1001Google Scholar
Crespi, M. G., Luzietti, L. and Marzario, M. (2008). Investigation in GNSS ground-based tropospheric tomography: benefits and perspectives of combined Galileo, Glonass and GPS constellations. Geophysical Research Abstracts, 10, EGU2008-A-03643Google Scholar
Davis, J. L., Herring, T. A., Shapiro, I. I., Rogers, A. E. E. and Elgered, G. (1985). Geodesy by radio interferometry: effects of atmospheric modeling errors on estimates of baseline length. Radio Science, 20(6), 1593–1607.CrossRefGoogle Scholar
Gardner, C. S. (1977). Correction of laser tracking data for the effects of horizontal refractivity gradients. Applied Optics, 16(9), 2427–2432.CrossRefGoogle ScholarPubMed
Ghoddousi-Fard, R. (2009). Modelling tropospheric gradients and parameters from NWP models: effects on GPS estimates. Ph.D. dissertation, University of New Brunswick, Canada.Google Scholar
Grgich, P. M., Kealy, A., Gordini, C., Hale, M. and Retscher, G. (2006). Atmospheric Bias Interpolation for Network RTK GPS. Proceedings of International Global Navigation Satellite Systems Society Symposium, Australia.Google Scholar
Haase, J., Ge, M., Vedel, H. and Calais, E. (2003). Accuracy and variability of GPS tropospheric delay measurements of water vapour in the western Mediterranean. Journal of Applied Meteorology, 42, 1547–1568.Google Scholar
Humphreys, T. E., Psiaki, M. L., Hinks, J. C., O'Hanlon, B. and JrKintner, P. M. (2009). Simulating Ionosphere Induced Scintillation for Testing GPS Receiver Phase Tracking Loops. IEEE Journal of Selected Topics in Signal Processing, 3(4), 707–715.Google Scholar
Ifadis, I. (1986). The atmospheric delay of radio waves: Modeling the elevation dependence on a global scale. Tech. Rep. 38L, Chalmers Univ. of Technol., Gothenburg, Sweden.Google Scholar
Karabatic, A., Weber, R. and Leroch, S. (2008). GNSSMET – Contribution of tropospheric zenith delays derived from GNSS data to weather forecast in alpine areas. Geophysical Research Abstracts, 10, EGU2008-A-02274Google Scholar
Kim, T., Conker, R. S., El-Arini, M. B., Ericson, S. D., Hegarty, C. J. and Tran, M. (2003). Preliminary Evaluation of the Effects of Scintillation on L5 GPS and SBAS Receivers Using a Frequency Domain Scintillation Model and Simulated and Analytical Receiver Models. Proceedings of the National Technical Meeting of the Satellite Division of the Institute of Navigation, 833–847, Anaheim, USA.Google Scholar
McCarthy, D. D. and Petit, G. (2003). IERS Conventions. International Earth Rotation and Reference Systems Service (IERS) Technical Note, 32.Google Scholar
Mendes, V. B. (1999). Modeling the Neutral-Atmosphere Propagation Delay in Radiometric Space Techniques. Ph.D. dissertation, University of New Brunswick, Canada.Google Scholar
Niell, A. E. (1996). Global mapping functions for the atmosphere delay at radio wavelengths. Journal of Geophysical Research, 101(B2), 3227–3246.CrossRefGoogle Scholar
Niell, A. E. (2000). Improved atmospheric mapping functions for VLBI and GPS. Earth Planets Space, 52, 699–702.Google Scholar
Orliac, E. J. (2009). Development of azimuth dependent tropospheric mapping functions, based on a high resolution mesoscale numerical weather model, for GNSS data processing. Ph.D. dissertation, University of Nottingham, UK.Google Scholar
Rocken, C., Sokolovskiy, S., Johnson, J. M. and Hunt, D. (2001). Improved mapping of tropospheric delay. Atmospheric and Oceanic Tech, 18, 1205–1213.Google Scholar
Saastamoinen, J. (1973). Contributions to the theory of atmospheric refraction, part II: refraction corrections in satellite geodesy. Bulletin Géodésique, 107, 13–34.CrossRefGoogle Scholar
Tregoning, P. and Herring, T. A. (2006). Impact of a priori zenith hydrostatic delay errors on GPS estimates of station heights and zenith total delays. Geophysical Research Letters, 33, ARTN L23303, doi:10.1029/2006GL027706CrossRefGoogle Scholar