A Regional Zenith Tropospheric Delay (ZTD) Model Based on GPT3 and ANN

Jun Li,Jiming Guo,Yitao Li,Fei Yang,Chaoyang Zhang

doi:10.3390/rs13050838

Abstract

The delays of radio signals transmitted by global navigation satellite system (GNSS) satellites and induced by neutral atmosphere, which are usually represented by zenith tropospheric delay (ZTD), are required as critical information both for GNSS positioning and navigation and GNSS meteorology. Establishing a stable and reliable ZTD model is one of the interests in GNSS research. In this study, we proposed a regional ZTD model that makes full use of the ZTD calculated from regional GNSS data and the corresponding ZTD estimated by global pressure and temperature 3 (GPT3) model, adopting the artificial neutral network (ANN) to construct the correlation between ZTD derived from GPT3 and GNSS observations. The experiments in Hong Kong using Satellite Positioning Reference Station Network (SatRet) were conducted and three statistical values, i.e., bias, root mean square error (RMSE), and compound relative error (CRE) were adopted for our comparisons. Numerical results showed that the proposed model outperformed the parameter ZTD model (Saastamoinen model) and the empirical ZTD model (GPT3 model), with an approximately 56%/52% and 52%/37% RMSE improvement in the internal and external accuracy verification, respectively. Moreover, the proposed method effectively improved the systematic deviation of GPT3 model and achieved better ZTD estimation in both rainy and rainless conditions.

Highlights

Accepted: 20 February 2021The radio signal is delayed and bent during its passage through the neutral atmosphere due to the interaction with water vapor particles and dry gases [1,2]
The zenith tropospheric delay (ZTD), which is projected from the slant tropospheric delay by using the mapping function, is a common parameter to describe the tropospheric influence on signal traveling
Method #2 had significant differences in the accuracy of ZTD estimation in rainless and rainy conditions, mainly in the following two aspects: (1) the biases of rainless days were positive and those of rainy days were negative, indicating that the ZTD estimated by global pressure and temperature 3 (GPT3) model in rainless conditions was relatively large while the estimate ZTD value was relatively small in rainy conditions; (2) the mean bias and root mean square error (RMSE) of rainless days were

Summary

Introduction

Accepted: 20 February 2021The radio signal is delayed and bent during its passage through the neutral atmosphere due to the interaction with water vapor particles and dry gases [1,2]. Establishing a stable and reliable zenith tropospheric delay (ZTD) model is one of the interests in GNSS research. On the basis of the relationship between the ZTD and meteorological parameters such as temperature, pressure, and water vapor pressure, researchers established a series of parameter ZTD models such as the Hopfield model, Saastamoinen model, and Black model [14,15,16]. These models can achieve ZTD values with centimeter-level accuracy by inputting accurate measured meteorological parameters [17,18]. Most GNSS sites are not equipped with meteorological sensors, and there are often no collocated weather

Methods

Findings

Discussion

Conclusion