A global empirical model for estimating zenith tropospheric delay
- 190 Downloads
Tropospheric delay acts as a systematic error source in the Global Navigation Satellite Systems (GNSS) positioning. Empirical models UNB3, UNB3m, UNB4 and EGNOS have been developed for use in Satellite-Based Augmentation Systems (SBAS). Model performance, however, is limited due to the low spatial resolution of the look-up tables for meteorological parameters. A new design has been established in this study for improving performance of the tropospheric delay model by more effectively eliminating the error produced by tropospheric delay. The spatiotemporal characteristics of the Zenith Tropospheric Delay (ZTD) were analyzed with findings that ZTD exhibits different annual variations at different locations and decreases exponentially with height increasing. Spherical harmonics are utilized based on the findings to fit the annual mean and amplitude of the ZTD on a global scale and the exponential function is utilized for height corrections, yielding the ZTrop model. On a global scale, the ZTrop features an average deviation of -1.0 cm and Root Mean Square (RMS) of 4.7 cm compared with the International GNSS Service (IGS) ZTD products, an average deviation of 0.0 cm and RMS of 4.5 cm compared with the Global Geodetic Observing System (GGOS) ZTD data, and an average deviation of -1.3 cm and RMS of 5.2 cm compared with the ZTD data from the Constellation Observing System of Meteorology, Ionosphere, and Climate (COSMIC). The RMS of the ZTrop model is 14.5% smaller than that of UNB3, 6.0% smaller than that of UNB3m, 16% smaller than that of UNB4, 14.5% smaller than that of EGNOS and equivalent to the sophisticated GPT2+Saas model in comparison with the IGS ZTD products. The ZTrop, UNB3m and GPT2+Saas models are finally evaluated in GPS-based Precise Point Positioning (PPP), as the models act to aid in obtaining PPP position error less than 1.5 cm in north and east components and relative large error (>5 cm) in up component with respect to the random walk approach.
Keywordszenith tropospheric delay spherical harmonics exponential function ZTrop model
Unable to display preview. Download preview PDF.
- Collins J P, Langley R B. 1997. A tropospheric delay model for the user of the Wide Area Augmentation System. Final contract report for Nav Canada, Department of Geodesy and Geomatics Engineering Technical Report No. 187, University of New Brunswick, Fredericton, N.B., CanadaGoogle Scholar
- Collins J P, Langley R B, LaMance J. 1996. Limiting factors in tropospheric propagation delay error modelling for GPS airborne navigation. Proceedings of the Institute of Navigation 52nd Annual Meeting, Cambridge, MA, USA, 19–21 June 1996. 519–528Google Scholar
- Collins J P, Langley R. 1998. The residual tropospheric propagation delay: How bad can it get? 11th International Technical Meeting of the Satellite Division of the Institute of Navigation, Nashville, Tennessee. ION GPS-98. 729–738Google Scholar
- Leandro R, Santos M C, Langley R B. 2006. UNB neutral atmosphere models: Development and performance. Proc ION NTM 2006, January 18–20, Monterey, California, USA. 564–573Google Scholar
- Mendes V. 1999. Modeling the neutral-atmospheric propagation delay in radiometric space techniques. Doctoral Dissertation. Brunswick: University of New BrunswickGoogle Scholar
- Jin S, Park J, Cho J, Park P. 2007. Seasonal variability of GPS-derived zenith tropospheric delay (1994–2006) and climate implications. J Geophys Res, 112: D09110Google Scholar
- Webb F H. 1993. An introduction to the GIPSY/OASIS II. JPL Publ, D-11088Google Scholar