Improving the stochastic model for VRS network-based GNSS surveying

• Autorzy: Jongrujinan Thanate , Satirapod Chalermchon

Identyfikatory

DOI

10.2478/arsa-2019-0003

• Języki publikacji: EN

Abstrakty

EN

The VRS network-based technique has become the main precise GNSS surveying method especially for medium-range baselines (approximately 20-70 km). The key concept of this approach is to use the observables of multiple reference stations to generate the network correction in the form of a virtual reference station for mitigating distance-dependent errors including atmospheric effects and orbital uncertainty at the user’s location. Numerous GNSS data processing strategies have been adopted in the functional model in order to improve both the positioning accuracy and the success of ambiguity resolution. However, it is impossible to completely model the aforementioned errors. As a result, the unmodelled residuals still remain in the virtual reference station observables when the least squares estimation is employed. An alternative approach to deal with these residuals is to construct a more realistic stochastic model whereby the variance-covariance matrix is assumed to be homoscedastic. This research aims to investigate a suitable stochastic model used for the VRS technique. The rigorous statistical method, MINQUE has been applied to estimate the variance-covariance matrix of the double-difference observables for a virtual reference station to rover baseline determination. The findings of the comparison to the equal-weight model and the satellite elevation-based model indicated that the MINQUE procedure could enhance the positioning accuracy. In addition, the reliability of ambiguity resolution is also improved.

Słowa kluczowe

EN

network-based RTK; VRS; stochastic model; MINQUE

• Wydawca: Centrum Badań Kosmicznych PAN ; De Gruyter
• Czasopismo: Artificial Satellites : Journal of Planetary Geodesy
• Rocznik: 2019
• Tom: Vol. 54, No. 1
• Strony: 17--30
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Jongrujinan Thanate

• Department of Survey Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

autor

Satirapod Chalermchon

• Department of Survey Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

Bibliografia

• Al-Shaery, A., Lim, S., & Rizos, C. (2011) Investigation of Different Interpolation Models Used in Network-RTK for the Virtual Reference Station Technique. Journal of Global Positioning Systems, 10, 136-148.
• Charoenkalunyuta, T., Satirapod, C., Li Y. and Rizos, C. (2012) An investigation of the effect of Ionospheric models on the performance of Network-based RTK GPS in Thailand. International Journal of Geoinformatics, 8(4), 61-66.
• Chen, H.Y., Rizos, C. and Han S., (2004) An instantaneous ambiguity resolution procedure suitable for medium-scale GPS reference station networks. Survey Review, 37(291), 396-410.
• De Jonge, P. and Tiberius C. (1995) The LAMBDA method for integer ambiguity estimation: implementation aspects. Publications of the Delft Computing Centre, LGR-Series 12 (12), 1-47.
• Jongrujinan, T. and Satirapod. C. (2018) Study on the stochastic model for VRS network-based GNSS positioning, Proceedings of ITC CSCC 2018, July 4-7, Bangkok, Thailand, paper 124.
• Landau, H. and Euler, H.J. (1992) On-the-Fly Ambiguity Resolution for Precise Differential Positioning. Proc. Of 5th Int. Tech. Meeting of the Satellite Division of the Institute of Navigation, Salt Lake City, Utah, 19-22 September, 1165-1171.
• Luo, X., Mayer, M., Heck, B., and Awange, J. (2014) A Realistic and Easy-to-Implement Weighting Model for GPS Phase Observations. IEEE Transactions on Geoscience and Remote sensing, 52(10), 6110-6118.
• Musa, T. A., Wang, J., Rizos, C., and Satirapod, C. (2003) Stochastic Modeling for Network-based GPS Positioning. The 6th International Symposium on Satellite Navigation Technology Including Mobile Positioning & Location Services, 22-25 July 2003 Melbourne, Australia.
• Odijik, D., (2000) Weighting Ionospheric Corrections to Improve Fast GPS Positioning Over Medium Distances. The ION GPS 2000, 19-22 September 2000,Salt Lake City, Utah, USA.
• Prochniewicz, D., Szpunar, R., & Brzezinski, A. (2016) Network-Based Stochastic Model for Instantaneous GNSS Real-Time Kinematic Positioning. Journal of Surveying Engineering, 142(4).
• Rao, C. R. (1971) Estimation of variance and covariance components-MINQUE theory. Journal of Multivariate Analysis, 1(3), 257-275.
• Satirapod, C., Wang, J., and Rizos, C. (2001) A New Stochastic Modelling Procedure for Precise Static GPS Positioning. Zeitschrift für Vermessungswesen, 126(6), 365-373.
• Satirapod, C., Wang, J. and Rizos, C. (2002) A simplified MINQUE procedure for the estimation of variance-covariance components of GPS observables. Survey Review, 35(286), 582-590.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).