A new global zenith tropospheric delay model IGGtrop for GNSS applications

Abstract

Tropospheric delay is one of the main sources of measurement error in global navigation satellite systems. It is usually compensated by using an empirical correction model. In this paper, temporal and spatial variations of the global zenith tropospheric delay (ZTD) are further analyzed by ZTD time series from global International GNSS Service stations and annual ZTDs derived from global National Centers for Environmental Prediction reanalysis data, respectively. A new ZTD correction model, named IGGtrop, is developed based on the characteristics of ZTD. Experimental results show that this new 3D-grid-based model that accommodates longitudinal as well as latitudinal variations of ZTD performs better than latitude-only based models (such as UNB3, EGNOS, and UNB3m). The global average bias and RMS for IGGtrop are about −0.8 cm and 4.0 cm, respectively. Bias values for UNB3, EGNOS, and UNB3m are 2.0, 2.0, and 0.7 cm, respectively, and respective RMS values 5.4, 5.4, and 5.0 cm. IGGtrop shows much more consistent prediction errors for different areas than EGNOS and UNB3m. In China, the performance of IGGtrop (bias values from −2.0 to 0.4 cm and RMS from 2.1 to 6.4 cm) is clearly superior to those of EGNOS and UNB3m. It is also demonstrated that IGGtrop biases vary little with height, and its RMS values tend to decrease with increasing height. In addition, IGGtrop generally estimates ZTD with greater accuracy than EGNOS and UNB3m in the Southern Hemisphere.

An improved global zenith tropospheric delay model GZTD2 considering diurnal variations

“…As can be seen from Fig. 3a, the coefficient a 0 in low latitudes, especially near the equator, is significantly larger than in high latitudes, and the distribution in the Southern Hemisphere is more uniform than in the Northern Hemisphere; these results are mostly in agreement with the results of Li et al (2012) and Yao et al (2013). For the sawtooth shape in the 40 • N-40 • S region, Yao et al (2013) found that this shape appears in coastal areas and is consistent with the directions of equatorial trade winds, so they assumed that the distributions of ZTD are effected by some physical impacts such as terrains and heat circulation.…”

“…Compared with the GZTD model, the range of bias of the GZTD2 model reduces by 2.4 cm and the maximum rms of the GZTD2 model decreases by 0.2 cm, indicating that the new model has a higher stability. Bias and rms of the EGNOS model are very close to those of the UNB3 model and both are worse than the UNB3m, which is similar to the results of Li et al (2012). To display the correction effects of different models in a more intuitive way, we computed the distributions of bias and rms of all IGS stations.…”

“…The traditional models like the Hopfield model (Hopfield, 1969), Saastamoinen model (Saastamoinen, 1973), and Black model (Black, 1978) require realtime meteorological data to reach a correction accuracy better than 10 cm. Given the location and time information, the UNB series models Langley, 1997, 1998;Leandro et al, 2006Leandro et al, , 2008 and the EGNOS model (Dodson et al, 1999;Penna et al, 2001;Ueno et al, 2001) use the empirical meteorological parameters in the form of the latitude band table to estimate the ZTD with an accuracy of about 5 cm, while the IGGTrop model (Li et al, 2012) is based on the empirical three-dimensional parameters in the form of grids to calculate the ZTD with an accuracy of about 4 cm. However, the IGGTrop model needs a large number of parameters.…”

SSIEGNOS: A New Asian Single Site Tropospheric Correction Model

“…This error becomes higher as the propagating direction deviates from the zenith towards the horizon direction and can reach approximately 20 m at the horizon direction [1]. Therefore, tropospheric delay must be effectively corrected when used for real-time GNSS navigation and positioning, especially when applied in GNSS real-time precise point positioning techniques [2,3].…”

A New Method to Accelerate PPP Convergence Time by using a Global Zenith Troposphere Delay Estimate Model

“…Li et al (2012) constructed the latest global empirical model IGGtrop with analysed data from the National Centers for Environmental Prediction (NCEP) thereby improving the accuracy. While by using spherical harmonic functions and global tropospheric delay grids data offered by the Global Geodetic Observing System (GGOS), Yao et al (2013) established a global ZTD model without meteorological parameters.…”