Validation of a New Model for the Estimation of Residual Tropospheric Delay Error Under Extreme Weather Conditions

Abstract

The electromagnetic signals of the Global Navigation Satellite Systems (GNSS) satellites suffer delays while propagating through the troposphere. The tropospheric delay is a significant systematic error of GNSS positioning. For safety-of-life applications of positioning many systematic error effects are either mitigated or eliminated in the positioning solution. Space based augmentation systems provide corrections for the orbital and satellite clock error, the ionospheric effects, etc. Moreover advanced GNSS provide dual frequency code observations for civilian users to eliminate the ionospheric delays caused by the electron content of the upper atmosphere. Nevertheless tropospheric delays are still taken into account using empirical models.For safety-of-life applications besides the accuracy of the positioning, the integrity of the positioning service is an important factor, too. The integrity information includes the maximal positioning error at an extremely rare probability level, called protection level to ensure highly reliable position solution in the aviation. The Radio Technical Commission for Aeronautics Minimum Operational Performance Standard (RTCA MOPS) recommends 0.12 m as the maximum zenith tropospheric error in terms of standard deviation. Previous studies show that this recommendation seems to be too conservative leading to a lower service availability. Therefore a more realistic integrity model has to be derived for the estimation of maximal residual tropospheric delay error.In the recent years many advanced empirical tropospheric delay models have been formulated compared to the one recommended by the RTCA. Recently new integrity models have been derived for estimating the maximum residual tropospheric delay error using numerical weather models under real extreme weather.The aim of this paper is to study the reliability of these models conditions. In order to achieve this, high-resolution numerical weather models were ray-traced using an improved ray-tracing algorithm to evaluate the slant and zenith tropospheric delays with the geographical resolution of 0.1° × 0.1°.

Precipitable Water Vapor Converted from GNSS-ZTD and ERA5 Datasets for the Monitoring of Tropical Cyclones

“…This is likely to be caused by active water vapor in summer. This result implies that, generally, the accuracy of the GNSS-ZTD is likely to be worse in summer [42]. Tables 3 and 4 show the statistics of the ground temperature and pressure values interpolated from the ERA5-and ERA5-P grids (with the sizes 0.25 • and 0.125 • ), respectively for the antenna positions of the aforementioned 15 GNSS stations that were equipped with meteorological sensors.…”

Tomographic Reconstruction of Atmospheric Water Vapor Profiles Using Multi-GNSS Observations

“…The water vapor content in the stratosphere is close to zero. The wet delay is more variable in both time and space [22,23] due to the highly variable water vapor distribution. Therefore, precise GNSS positioning techniques account for the hydrostatic part of the delay as a correction, while the wet component is estimated using the GNSS observations.…”

Considering Variances of Quasi-Random Effects in Relative GPS Positioning Performed During Daytime and Nighttime Periods – A Novel Two-Stage Approach

“…But, in each of them these effects were treated individually and a reader can be referred to the recent ones, such as, e.g. Hu et al (2015), Deng et al (2016), Elsobeiey and El-Diasty (2016), Jadviščok et al (2016), Klos et al (2018), Zhou et al (2018), Anđić, (2019b), Han et al (2019), Juni and Rózsa (2019), Kallio et al (2019).…”