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Investigations into Phase Multipath Mitigation Techniques for High Precision Positioning in Difficult Environments

Published online by Cambridge University Press:  09 August 2007

Lawrence Lau*
Affiliation:
(University College London)
Paul Cross
Affiliation:
(University College London)

Abstract

The modelling of most Global Navigation Satellite System (GNSS) errors/biases and developments of data processing techniques have been improved substantially since the birth of Global Positioning System (GPS), however, there has been much less progress in the improvement of phase multipath mitigation techniques. Multipath therefore remains one of the most important error sources in high precision GNSS positioning. This is because multipath is site-dependent and therefore cannot be eliminated by differencing techniques. Also multipath is highly dependent on satellite-reflector-antenna geometry, which usually causes rapid changes in phase multipath errors especially in Real-Time Kinematic (RTK) applications. Multipath mitigation for static antennas such as those at reference stations can be carried out by site calibration, averaging over long observation times, and through the estimation of the error using filtering based on signal-to-noise ratio (SNR) data. However, multipath mitigation for kinematic antennas is still very difficult today.

Nevertheless, much research has been carried out on a particular class of phase multipath mitigation techniques: ones that can be applied within positioning algorithms (rather than incorporated into the receiver tracking loops or antennas). This paper investigates and further develops a number of state-of-the-art techniques in this category. They include phase multipath estimation using SNR data, phase multipath estimation through the use of closely spaced antennas, multipath mitigation stochastic models such as the satellite elevation angle model and SNR-based models (SIGMA-∊ model and our modified SNR-based model), and our own novel ray-tracing method. The techniques are tested with both real and simulated data, the real test datasets have been collected on the Laboratoire Central des Ponts et Chaussées (LCPC) testbed near Nantes in France, and on the campus of the University of Nottingham during SPACE data collection experiments.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2007

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References

Bar-Shalom, Y., Li, X. R., and Kirubarajan, T. (2001). Estimation with Applications to Tracking and Navigation, 1st Edition, Wiley-Interscience, ISBN 047141655X.Google Scholar
Barnes, J. B., Ackroyd, N., and Cross, P. A. (1998). Stochastic Modelling for Very High Precision Real-Time Kinematic GPS in an Engineering Environment. Proceedings of FIG XXI International Conference, 21–25 July, Brighton, UK, Commission 6, 6176.Google Scholar
Bétaille, D. (2004). Assessment and Improvement of the Capabilities of a Window Correlator to Model GPS Multipath Phase Errors. PhD Thesis, Department of Geomatic Engineering, University College London, University of London.Google Scholar
Bétaille, D., Cross, P. A. and Euler, H-J (2006). Assessment and improvement of the capabilities of a window correlator to model GPS multipath phase errors. IEEE Transactions on Aerospace and Electronic Systems. Vol. 42, No. 2, 707718.CrossRefGoogle Scholar
Brown, A. (2001). High Accuracy GPS Performance using a Digital Adaptive Antenna Array. Proceedings of ION National Technical Meeting 2001, Long Beach, CA, January 2001, 335343.Google Scholar
Brown, A, Wang, J (1999). High Accuracy Kinematic GPS Performance Using A Digital Bean-Steering Array. Proceedings of ION GPS 99, Nashville, TN, 14–17 September, 16851693.Google Scholar
Brown, R. G. and Hwang, P. Y. C. (1996). Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions. 3rd Edition, Wiley, ISBN 0471128392.Google Scholar
Collins, J. P. and Langley, R. B. (1999). Possible Weighting Schemes for GPS Carrier Phase Observations in the Presence of Multipath. Technical Report, Geodetic Research Laboratory, Department of Geodesy and Geomatics Engineering, University of New Brunswick, Report No. TCN 98151.Google Scholar
Comp, C. J., Axelrad, P. (1996). An Adaptive SNR-based Carrier Phase Multipath Mitigation Technique. Proceedings of ION GPS-96, The Institute of Navigation, Kansas City, Missouri, 683697.Google Scholar
Cross, P. A. (2002), Pseudorange Multipath Error. Lecture Note, GEOMG 029, Lecture 2–1. Department of Geomatic Engineering, University College London.Google Scholar
Ghose, R. N. (1996). Interference Mitigation: Theory and Application. IEEE Press, ISBN 0780311310.Google Scholar
Gratton, L, Khanafseh, S, Pervan, B, Pullen, S, Warburton, J (2004). Experimental Observations and Integrity Monitor Applications of LAAS IMLA Carrier Phase Measurements. Proceedings of ION GNSS 2004, Long Beach, CA, 21–24 September, 22592270.Google Scholar
Händel, P. and Tichavský, P. (1994). Adaptive Estimation for Periodic Signal Enhancement and Tracking. International Journal of Adaptive Control and Signal Processing, Vol. 8, 447456.CrossRefGoogle Scholar
Hartinger, H., Brunner, F. K. (1999). Variances of GPS Phase Observations: The SIGMA-ε Model. GPS Solutions, 2(4), 3543.Google Scholar
Kim, D, Jang, J., Kee, C. (2004). Integer Ambiguity Search Technique Using Separated Gaussian Variables. Proceedings of The 2004 International Symposium on GNSS/GPS, Sydney, Australia, 6–8 December.Google Scholar
Park, J. G., Kim, J., Lee, J. G., Park, C., Jee, G., Oh, J. T. (1998). The Enhancement of INS Alignment Using GPS Measurements. Proceedings of Position Location and Navigation Symposium, IEEE, Palm Springs, CA, 20–23 April, pp 534540. ISBN:0780343301, DOI:10.1109/PLANS.1998.670209CrossRefGoogle Scholar
Lau, L. (2004). Investigations into Multipath Effects on GNSS Multiple-Frequency Single Epoch High Precision Positioning. Proceedings of ION GNSS 2004, The Institute of Navigation, Long Beach, California, 21–24 September 2004, 11691180.Google Scholar
Lau, K. Y. L. (2005). Phase Multipath Modelling and Mitigation in Multiple Frequency GPS and Galileo Positioning. PhD Thesis, Department of Geomatic Engineering, University College London, University of London.Google Scholar
Lau, L. and Cross, P. (2005). Use of Signal-to-Noise Ratios for Real-Time GNSS Phase Multipath Mitigation. Nav05, Royal Institute of Navigation, Church House, London, 1–3 November, 2005.Google Scholar
Lau, L., Cross, P. (2006a). Prospects for Phase Multipath Mitigation Using Antenna Arrays for Very High Precision Real-Time Kinematic Applications in the Presence of New GNSS Signals. Proceedings of The European Navigation Conference 2006, 8–10 May, Manchester, UK.Google Scholar
Lau, L., Cross, P. (2006b). A New Signal-to-Noise-Ratio Based Stochastic Model for GNSS High-Precision Carrier Phase Data Processing Algorithms in the Presence of Multipath Errors. Proceedings of ION GNSS 2006, September 26–29. Fort Worth, Texas.Google Scholar
Lau, L. and Cross, P. (2007). Development and Testing of a New Rigorous Ray Tracing Approach to GNSS Carrier Phase Multipath Modelling. In review for Journal of Geodesy.CrossRefGoogle Scholar
Ray, J. K. (2000). Mitigation of GPS Code and Carrier Phase Multipath Effects Using a Multi-Antenna System. PhD Thesis, Department of Geomatics Engineering, University of Calgary.Google Scholar
Regalia, P. (1994). Adaptive IIR Filtering in Signal Processing and Control. Marcel Dekker, INC., ISBN 0824792890.Google Scholar