Improved Troposphere Blind Models Based on Numerical Weather Data

Gregor Möller, Robert Weber, and Johannes Böhm

Peer Reviewed

Abstract: The troposphere blind model RTCA MOPS is the minimum operational performance standard for global positioning systems. With a standard deviation of 2.3% of the ZTD, it enables us to mitigate the main part of the tropospheric effect on GNSS signals. Nevertheless, the comparison of RTCA MOPS with modern troposphere models like the ESA model or GPT2 shows the limitation of RTCA MOPS and points out the potential of modern troposphere blind models based on climatological series derived from numerical weather data. The ESA model profits from a more advanced wet delay model and a higher spatial resolution. GPT2 shows the smallest mean bias on surface level in comparison to ray-tracing and IGS data and profits from additional mapping function coefficients – especially if the user is interested in tropospheric delay at low elevation angles. A revision of GPT2 - called GPT2w - combines the benefits of both aforementioned models.
Published in: NAVIGATION, Journal of the Institute of Navigation, Volume 61, Number 3
Pages: 203 - 211
Cite this article: Möller, Gregor, Weber, Robert, Böhm, Johannes, "Improved Troposphere Blind Models Based on Numerical Weather Data", NAVIGATION, Journal of The Institute of Navigation, Vol. 61, No. 3, Fall 2014, pp. 203-211.
https://doi.org/10.1002/navi.66
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