scholarly journals GEODESY, CARTOGRAPHY AND AERIAL PHOTOGRAPHY

2021 ◽  
Vol 94, 2021 (94) ◽  
pp. 13-19
Author(s):  
Fedir Zablotskyi ◽  
◽  
Bohdan Palianytsia ◽  
Bohdan Kladochnyi ◽  
Olena Nevmerzhytska ◽  
...  
Keyword(s):  
Reference Station ◽  
Tropospheric Delay ◽  
Atmospheric Models ◽  
Time Intervals ◽  
Zenith Tropospheric Delay ◽  
Radio Sounding ◽  
Systematic Shift ◽  
Gnss Measurements ◽  
Hydrostatic Component

The aim of this work is to evaluate the accuracy of determining the wet component of zenith tropospheric delay (ZTD) from GNSS-measurements and the accuracy of determining the hydrostatic component according to the Saastamoinen model in comparison with the radio sounding data as well. Zenith tropospheric delay is determined mainly by two methods - traditional, using radio sounding or using atmospheric models, such as the Saastamoinen model, and the method of GNSS measurements. Determination of the hydrostatic component of the zenith tropospheric delay was performed by radio sounding data obtained at the aerological station Praha-Libus in 2011-2013 and in 2018. Data were processed for the middle decades of January and July of each year at 0h o’clock of the Universal Time. The wet component was calculated from GNSS observations. By a significant number of radio soundings at the Praha-Libus aerological station, hydrostatic and wet components of zenith tropospheric delay (ZTD) and the same number of ZTD values derived for the corresponding time intervals from GNSS measurements at the GOPE reference station were determined. The values of the wet component of ZTD were determined and compared with the corresponding data obtained from radio soundings. We found that the error of the hydrostatic component in winter does not exceed 10 mm in absolute value, and in summer it is approximately 1.5 times smaller. This is due to differences in the stratification of the troposphere and lower stratosphere in winter and summer. As for the wet component of ZTD, its errors do not exceed: in winter 15 mm, in summer – 35 mm. The resulting differences in summer have a negative sign, indicating a systematic shift, and in winter – both negative and positive. Today, there are many studies aimed at improving the accuracy of determining zenith tropospheric delay by both Ukrainian and foreign authors, but the problem of the accuracy of the hydrostatic component remains open. The study provides recommendations for further research to improve the accuracy of zenith tropospheric delay.

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

2021 ◽  
Vol 13 (5) ◽  
pp. 838
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Chaoyang Zhang ◽  
Yitao Li ◽  
Jun Li
Keyword(s):  
Satellite System ◽  
Reference Station ◽  
Tropospheric Delay ◽  
Neutral Atmosphere ◽  
Zenith Tropospheric Delay ◽  
Satellite Positioning ◽  
Proposed Model ◽  
Radio Signals ◽  
Global Navigation Satellite ◽  
Gnss Data

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.

scholarly journals Regional Zenith Tropospheric Delay Modeling Based on Least Squares Support Vector Machine Using GNSS and ERA5 Data

2021 ◽  
Vol 13 (5) ◽  
pp. 1004
Author(s):  
Song Li ◽  
Tianhe Xu ◽  
Nan Jiang ◽  
Honglei Yang ◽  
Shuaimin Wang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
High Efficiency ◽  
Rapid Development ◽  
Support Vector ◽  
Tropospheric Delay ◽  
Improvement Rate ◽  
Zenith Tropospheric Delay ◽  
Background Data ◽  
Mean Square Errors

The meteorological reanalysis data has been widely applied to derive zenith tropospheric delay (ZTD) with a high spatial and temporal resolution. With the rapid development of artificial intelligence, machine learning also begins as a high-efficiency tool to be employed in modeling and predicting ZTD. In this paper, we develop three new regional ZTD models based on the least squares support vector machine (LSSVM), using both the International GNSS Service (IGS)-ZTD products and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data over Europe throughout 2018. Among them, the ERA5 data is extended to ERA5S-ZTD and ERA5P-ZTD as the background data by the model method and integral method, respectively. Depending on different background data, three schemes are designed to construct ZTD models based on the LSSVM algorithm, including the without background data, with the ERA5S-ZTD, and with the ERA5P-ZTD. To investigate the advantage and feasibility of the proposed ZTD models, we evaluate the accuracy of two background data and three schemes by segmental comparison with the IGS-ZTD of 85 IGS stations in Europe. The results show that the overall average Root Mean Square Errors (RMSE) value of all sites is 30.1 mm for the ERA5S-ZTD, and 10.7 mm for the ERA5P-ZTD. The overall average RMSE is 25.8 mm, 22.9 mm, and 9 mm for the three schemes, respectively. Moreover, the overall improvement rate is 19.1% and 1.6% for the ZTD model with ERA5S-ZTD and ERA5P-ZTD, respectively. In order to explore the reason of the lower improvement for the ZTD model with ERA5P-ZTD, the loop verification is performed by estimating the ZTD values of each available IGS station. In actuality, the monthly improvement rate of estimated ZTD is positive for most stations, and the biggest improvement rate can even reach about 40%. The negative rate mainly comes from specific stations, these stations are located on the edge of the region, near the coast, as well as the lower similarity between the individual verified station and training stations.

scholarly journals A New Zenith Tropospheric Delay Grid Product for Real-Time PPP Applications over China

Sensors ◽  
2017 ◽  
Vol 18 (2) ◽  
pp. 65 ◽  
Author(s):  
Yidong Lou ◽  
Jinfang Huang ◽  
Weixing Zhang ◽  
Hong Liang ◽  
Fu Zheng ◽  
...  
Keyword(s):  
Real Time ◽  
Tropospheric Delay ◽  
Zenith Tropospheric Delay

Radio-sounding data for the determination of the infra-red sky radiation

1988 ◽  
Vol 5 (4) ◽  
pp. 353-363 ◽  
Author(s):  
X. Berger ◽  
B. Cubizolles ◽  
I. Donet
Keyword(s):  
Radio Sounding ◽  
Infra Red

scholarly journals Empirical correction techniques: analysis and applications to chaotically driven low-order atmospheric models

2013 ◽  
Vol 20 (2) ◽  
pp. 199-206
Author(s):  
I. Trpevski ◽  
L. Basnarkov ◽  
D. Smilkov ◽  
L. Kocarev
Keyword(s):  
Linear Regression Method ◽  
Atmospheric Models ◽  
Time Intervals ◽  
Average Value ◽  
Climate Forecasting ◽  
Empirical Correction ◽  
Weather And Climate ◽  
Real World Applications ◽  
Correction Terms ◽  
Low Order

Abstract. Contemporary tools for reducing model error in weather and climate forecasting models include empirical correction techniques. In this paper we explore the use of such techniques on low-order atmospheric models. We first present an iterative linear regression method for model correction that works efficiently when the reference truth is sampled at large time intervals, which is typical for real world applications. Furthermore we investigate two recently proposed empirical correction techniques on Lorenz models with constant forcing while the reference truth is given by a Lorenz system driven with chaotic forcing. Both methods indicate that the largest increase in predictability comes from correction terms that are close to the average value of the chaotic forcing.

scholarly journals Determination of the Precise Coordinates of the GPS Reference Station in of a GBAS System in the Air Transport

2020 ◽  
Vol 22 (3) ◽  
pp. 11-18
Author(s):  
Kamil Krasuski ◽  
Stepan Savchuk
Keyword(s):  
Mathematical Model ◽  
Measurement Technique ◽  
Air Transport ◽  
Reference Station ◽  
The Real ◽  
Station Coordinates ◽  
Geocentric Coordinates

This paper presents results of research concerning determination of the GPS reference station coordinates located on the grounds of an EPDE airport in Deblin. The study uses a mathematical model of the PPP measurement technique in order to determine the coordinates of the reference station using the real GPS code-phase observations. The computations of the coordinates of the GPS reference station were carried out in numerical applications CSRS-PPP, APPS and GAPS. In this research was found that the accuracy of finding solutions to the XYZ geocentric coordinates of the reference station REF1 between solutions CSRS-PPP, APPS and GAPS ranges from 0.01m to 0.13m. In addition, the accuracy of determining the XYZ geocentric coordinates from the PPP method related to the GPS differential solution ranged from 0.01m to 0.11m.

Sign in / Sign up

Export Citation Format

Share Document