scholarly journals Establishment of a Real-Time Local Tropospheric Fusion Model

2019 ◽  
Vol 11 (11) ◽  
pp. 1321 ◽  
Author(s):  
Yibin Yao ◽  
Xingyu Xu ◽  
Chaoqian Xu ◽  
Wenjie Peng ◽  
Yangyang Wan
Keyword(s):  
Real Time ◽  
Meteorological Data ◽  
Rapid Development ◽  
Water Vapor Pressure ◽  
Auxiliary Information ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Navigation Systems ◽  
Delay Model ◽  
Fusion Model

The tropospheric delay is one major error source affecting the precise positioning provided by the global navigation satellite system (GNSS). This error occurs because the GNSS signals are refracted while travelling through the troposphere layer. Nowadays, various types of model can produce the tropospheric delay. Among them, the globally distributed GNSS permanent stations can resolve the tropospheric delay with the highest accuracy and the best continuity. Meteorological models, such as the Saastamoinen model, provide formulae to calculate temperature, pressure, water vapor pressure and subsequently the tropospheric delay. Some grid-based empirical tropospheric delay models directly provide tropospheric parameters at a global scale and in real time without any auxiliary information. However, the spatial resolution of the GNSS tropospheric delay is not sufficient, and the accuracy of the meteorological and empirical models is relatively poor. With the rapid development of satellite navigation systems around the globe, the demand for real-time high-precision GNSS positioning services has been growing dramatically, requiring real-time and high-accuracy troposphere models as a critical prerequisite. Therefore, this paper proposes a multi-source real-time local tropospheric delay model that uses polynomial fitting of ground-based GNSS observations, meteorological data, and empirical GPT2w models. The results show that the accuracy in the zenith tropospheric delay (ZTD) of the proposed tropospheric delay model has been verified with a RMS (root mean square) of 1.48 cm in active troposphere conditions, and 1.45 cm in stable troposphere conditions, which is significantly better than the conventional tropospheric GPT2w and Saastamoinen models.

scholarly journals Accuracy Assessment Study of UNB3m Neutral Atmosphere Model for Global Tropospheric Delay Mitigation

2015 ◽  
Vol 50 (4) ◽  
pp. 201-215
Author(s):  
Ashraf Farah
Keyword(s):  
Accuracy Assessment ◽  
Meteorological Data ◽  
Empirical Models ◽  
Water Vapour Pressure ◽  
Tropospheric Delay ◽  
Navigation Systems ◽  
Neutral Atmosphere ◽  
Positioning Errors ◽  
Assessment Study ◽  
Meteorological Models

Abstract Tropospheric delay is the second major source of error after the ionospheric delay for satellite navigation systems. The transmitted signal could face a delay caused by the troposphere of over 2m at zenith and 20m at lower satellite elevation angles of 10 degrees and below. Positioning errors of 10m or greater can result from the inaccurate mitigation of the tropospheric delay. Many techniques are available for tropospheric delay mitigation consisting of surface meteorological models and global empirical models. Surface meteorological models need surface meteorological data to give high accuracy mitigation while the global empirical models need not. Several hybrid neutral atmosphere delay models have been developed by (University of New Brunswick, Canada) UNB researchers over the past decade or so. The most widely applicable current version is UNB3m, which uses the Saastamoinen zenith delays, Niell mapping functions, and a look-up table with annual mean and amplitude for temperature, pressure, and water vapour pressure varying with respect to latitude and height. This paper presents an assessment study of the behaviour of the UNB3m model compared with highly accurate IGS-tropospheric estimation for three different (latitude/height) IGS stations. The study was performed over four nonconsecutive weeks on different seasons over one year (October 2014 to July 2015). It can be concluded that using UNB3m model gives tropospheric delay correction accuracy of 0.050m in average for low latitude regions in all seasons. The model's accuracy is about 0.075m for medium latitude regions, while its highest accuracy is about 0.014m for high latitude regions.

scholarly journals Empirical Orthogonal Function Analysis and Modeling of Global Tropospheric Delay Spherical Harmonic Coefficients

2021 ◽  
Vol 13 (21) ◽  
pp. 4385
Author(s):  
Yongchao Ma ◽  
Hang Liu ◽  
Guochang Xu ◽  
Zhiping Lu
Keyword(s):  
Empirical Orthogonal Function ◽  
Spherical Harmonic ◽  
Function Analysis ◽  
Meteorological Data ◽  
Regional Scale ◽  
Global Scale ◽  
Tropospheric Delay ◽  
Delay Model ◽  
Product Model ◽  
Orthogonal Function

Based on the ERA-5 meteorological data from 2015 to 2019, we establish the global tropospheric delay spherical harmonic (SH) coefficients set called the SH_set and develop the global tropospheric delay SH coefficients empirical model called EGtrop using the empirical orthogonal function (EOF) method and periodic functions. We apply tropospheric delay derived from IGS stations not involved in modeling as reference data for validating the dataset, and statistical results indicate that the global mean Bias of the SH_set is 0.08 cm, while the average global root mean square error (RMSE) is 2.61 cm, which meets the requirements of the tropospheric delay model applied in the wide-area augmentation system (WAAS), indicating the feasibility of the product strategy. The tropospheric delay calculated with global sounding station and tropospheric delay products of IGS stations in 2020 are employed to validate the new product model. It is verified that the EGtrop model has high accuracy with Bias and RMSE of −0.25 cm and 3.79 cm, respectively, with respect to the sounding station, and with Bias and RMSE of 0.42 cm and 3.65 cm, respectively, with respect to IGS products. The EGtrop model is applicable not only at the global scale but also at the regional scale and exhibits the advantage of local enhancement.

scholarly journals Monitoring Climate Changes on Small Scale Networks Using Ground Based GPS and Meteorological Data

2014 ◽  
Vol 49 (3) ◽  
pp. 125-135 ◽  
Author(s):  
C. Pikridas
Keyword(s):  
Climate Model ◽  
Meteorological Data ◽  
Water Vapor Pressure ◽  
Small Scale ◽  
Tropospheric Delay ◽  
Time Interval ◽  
Data Set ◽  
Multiple Stepwise Regression Analysis ◽  
Delay Variations ◽  
Gps Station

Abstract The total zenith tropospheric delay (ZTD) and its components, hydrostatic and wet parts are important parameters of the atmosphere and directly or indirectly reflect climate processes. This possibility can be more adaptive when meteorological data are combined to co-located meteorological sensors with GPS stations. In this paper eighteen months with one hour time interval ZTD estimates of a permanent GPS station are analyzed with the associated atmospheric parameters provided from a co-located meteorological sensor. The mathematical relationship through the multiple stepwise regression analysis reflects the plausible physical link of temperature and relative humidity values with ZTD’s. This regression equation is assessed by a second data set performed by a small GPS baseline few months later for the same study area. It was found that mainly due to the zenith wet delay variations and with the help of fundamental meteorological equations the behavior of water vapor pressure can be monitored and estimated. This is possible when an appropriate setup of GPS stations and a co-located meteorological sensor exist and if the GPS stations sound the same part of atmosphere. Therefore, the GPS tropospheric products are good indicators for a climate monitoring tool and can help address the physics of a climate model.

scholarly journals Performance Evaluation of Real-Time Precise Point Positioning with Both BDS-3 and BDS-2 Observations

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6027
Author(s):  
Lin Pan ◽  
Xuanping Li ◽  
Wenkun Yu ◽  
Wujiao Dai ◽  
Cuilin Kuang ◽  
...  
Keyword(s):  
Real Time ◽  
Precise Point Positioning ◽  
Rapid Development ◽  
Satellite System ◽  
Convergence Time ◽  
Static Mode ◽  
The Real ◽  
Point Positioning ◽  
Time Critical

For time-critical precise applications, one popular technology is the real-time precise point positioning (PPP). In recent years, there has been a rapid development in the BeiDou Navigation Satellite System (BDS), and the constellation of global BDS (BDS-3) has been fully deployed. In addition to the regional BDS (BDS-2) constellation, the real-time stream CLK93 has started to support the BDS-3 constellation, indicating that the real-time PPP processing involving BDS-3 observations is feasible. In this study, the global positioning performance of real-time PPP with BDS-3/BDS-2 observations is initially evaluated using the datasets from 147 stations. In the east, north and upward directions, positioning accuracy of 1.8, 1.2 and 2.5 cm in the static mode, and of 6.7, 5.1 and 10.4 cm in the kinematic mode can be achieved for the BDS-3/BDS-2 real-time PPP, respectively, while the corresponding convergence time with a threshold of 10 cm is 32.9, 23.7 and 32.8 min, and 66.9, 42.9 and 69.1 min in the two modes in the three directions, respectively. To complete this, the availability of BDS-3/BDS-2 constellations, the quality of BDS-3/BDS-2 real-time precise satellite products, and the BDS-3/BDS-2 post-processed PPP solutions are also analyzed. For comparison, the results for the GPS are also presented.

Multi-GNSS real-time orbit and clock quality changes over time 

2021 ◽  
Author(s):  
Kamil Kazmierski ◽  
Radoslaw Zajdel ◽  
Krzysztof Sośnica
Keyword(s):  
Real Time ◽  
Orbital Plane ◽  
Satellite System ◽  
Quality Level ◽  
Navigation Systems ◽  
Positioning Errors ◽  
Time Regime ◽  
Changes Over Time ◽  
Strategy Changes

<p>Navigation systems have substantially evolved in the last decade. The multi-GNSS constellation including GPS, GLONASS, Galileo, and BeiDou consists of more than a hundred active satellites. To fully exploit their potential, users should be able to take advantage of those systems not only in postprocessing mode employing final solutions but also in real-time. It is also important to make satellite signals highly useful in a real-time regime not only in standard positioning mode but also with the precise positioning technique. That is why real-time products are highly desirable. One of the IGS Analysis Centers that support multi-GNSS real-time solution is CNES which provides not only orbits and clocks but also code and phase biases and VTEC global maps. Over the last few years, real-time products have been changing similarly to navigation systems, which come along with observation availability and calculation strategy changes.</p><p>We utilize the signal-in-space ranging error (SISRE) as the main orbit and clock quality indicator. Additionally, SLR observations are used as an independent source of information about orbit quality. Three years of data, between 2017 and 2020, are used to check the progress in the quality of the delivered products to the users through the internet streams provided by CNES.</p><p>The progress in the product quality in the test period is obvious and it depends on the satellite system, block or satellite type, time, and the height of the Sun above the orbital plane. The most accurate orbits are available for GPS, however, the very stable atomic clocks of Galileo compensate for systematic errors in Galileo orbits. Consequently, the SISRE for Galileo is lower than that for GPS, equaling 1.6 and 2.3 cm for Galileo and GPS, respectively. The SISRE value for GLONASS, despite the good quality of the orbits, is disturbed by the lower quality of the onboard clocks and is equal to 4-6 cm. The same quality level is for BeiDou-2 MEO and IGSO satellites. Products for BeiDou-2 GEO satellites are less accurate and with poor availability due to a large number of satellite maneuvers, thus they are not very useful for real-time positioning.</p><p>For positioning purposes, the presented results may be interesting especially in the context of the proper observation weighting in the multi-GNSS combinations. It is worth mentioning that the quality of the real-time products is not constant and neglecting this fact may bring undesirable positioning errors, especially for long processing campaigns.</p>

scholarly journals Evaluation of the Possibility of Using the Predicted Tropospheric Delays in Real Time Gnss Positioning

2014 ◽  
Vol 49 (4) ◽  
pp. 179-189 ◽  
Author(s):  
J. Z. Kalita ◽  
Z. Rzepecka ◽  
G. Krzan
Keyword(s):  
Real Time ◽  
Satellite System ◽  
Weather Data ◽  
Observation System ◽  
Tropospheric Delay ◽  
Systematic Bias ◽  
Atmospheric Conditions ◽  
Predicted Values ◽  
Delay Component ◽  
Many Sources

ABSTRACT Among many sources of errors that influence Global Navigation Satellite System (GNSS) observations, tropospheric delay is one of the most significant. It causes nonrefractive systematic bias in the observations on the level of several meters, depending on the atmospheric conditions. Tropospheric delay modelling plays an important role in precise positioning. The current models use numerical weather data for precise estimation of the parameters that are provided as a part of the Global Geodetic Observation System (GGOS). The purpose of this paper is to analyze the tropospheric data provided by the GGOS Atmosphere Service conducted by the Vienna University of Technology. There are predicted and final delay data available at the Service. In real time tasks, only the predicted values can be used. Thus it is very useful to study accuracy of the forecast delays. Comparison of data sets based on predicted and real weather models allows for conclusions concerning possibility of using the former for real time positioning applications. The predicted values of the dry tropospheric delay component, both zenith and mapped, can be safely used in real time PPP applications, but on the other hand, while using the wet predicted values, one should be very careful.

Evaluation of EGNOS Tropospheric Delay Model in South-Eastern Europe

2009 ◽  
Vol 62 (2) ◽  
pp. 341-349 ◽  
Author(s):  
Tomislav Kos ◽  
Maja Botincan ◽  
Ivan Markezic
Keyword(s):  
Real Time ◽  
Meteorological Parameters ◽  
Prediction Models ◽  
Signal Propagation ◽  
Electromagnetic Signal ◽  
Tropospheric Delay ◽  
Delay Model ◽  
Signal Delay ◽  
One Year ◽  
Delay Prediction

The troposphere affects electromagnetic signal propagation causing signal path bending and the alteration of the electromagnetic wave velocity. Tropospheric delay can introduce a considerable error in satellite positioning if it is not properly estimated. The GPS signal delay can vary from 2 to 20 m depending on the elevation angles between the receiver and the satellite. Two basic types of delay prediction models exist. The first use surface meteorological parameters to estimate the value of the tropospheric delay, and the other models that do not require real-time meteorological input use average and seasonal variation data related to the receiver's latitude and day-of-year. This paper compares the performance of both types of model over a period of one year, comprising all seasons, to verify their accuracy over a longer period. The Saastamoinen model, known as one of the best performing prediction models, was taken as a reference and the global EGNOS model was used to check how the global estimates of the yearly averages of the meteorological parameters and their related seasonal variations comply with the real-time surface parameters.

scholarly journals A New Method for Estimating Tropospheric Zenith Wet-Component Delay of GNSS Signals from Surface Meteorology Data

2020 ◽  
Vol 12 (21) ◽  
pp. 3497
Author(s):  
Pengfei Xia ◽  
Jingchao Xia ◽  
Shirong Ye ◽  
Caijun Xu
Keyword(s):  
Weather Forecasting ◽  
Integral Formula ◽  
Meteorological Data ◽  
Weighted Average ◽  
Satellite System ◽  
Specific Humidity ◽  
Radiosonde Data ◽  
Weather Data ◽  
Tropospheric Delay ◽  
Radiosonde Observation

A new concept is proposed for estimating the zenith wet delay (ZWD) and atmospheric weighted average temperature by inputting the temperature, total pressure, and specific humidity from surface weather data. In addition, a new ZWD integral method is described for highly accurate calculation of the ZWD from radiosonde observation. To evaluate the advantages of the new discrete integral formula, we utilized the 8-year radiosonde profiles of 85 stations in China from 2010 to 2017 to validate the accuracy of the radiosonde-derived ZWD. The results showed that the mean accuracy of the ZWD derived from radiosonde data was 4.28 mm. Next, the new ZWD model was assessed using two sets of reference values derived from radiosonde data and GNSS precise point positioning in China. The results confirm that the new development improved the accuracy of the estimation of the tropospheric wet delay from the surface meteorological data. The performance of this new model can be seen as an important step toward accurately correcting the tropospheric delay in Global Navigation Satellite System (GNSS) real-time navigation and positioning. It can also be used in GNSS meteorology for weather forecasting and climate research.

scholarly journals SHAtropE—A Regional Gridded ZTD Model for China and the Surrounding Areas

2020 ◽  
Vol 12 (1) ◽  
pp. 165 ◽  
Author(s):  
Junping Chen ◽  
Jungang Wang ◽  
Ahao Wang ◽  
Junsheng Ding ◽  
Yize Zhang
Keyword(s):  
Meteorological Data ◽  
Grid Point ◽  
Mainland China ◽  
Propagation Delay ◽  
Convergence Time ◽  
Tropospheric Delay ◽  
Delay Model ◽  
Observation Network ◽  
Surrounding Areas ◽  
Improved Accuracy

A regional zenith tropospheric delay (ZTD) empirical model, referred to as SHAtropE (SHanghai Astronomical observatory tropospheric delay model—Extended), is developed and provides tropospheric propagation delay corrections for users in China and the surrounding areas with improved accuracy. The SHAtropE model was developed based on the ZTD time series of the continuous GNSS sites from the Crustal Movement Observation Network of China (CMONOC) and GNSS sites of surrounding areas. It combines the exponential and periodical functions and is provided as regional grids with a resolution of 2.5° × 2.0° in longitude and latitude. At each grid point, the exponential function converts the ZTD from the site height to the ellipsoid, and the periodical terms, including both annual and semi-annual periods, describe ZTD’s temporal variation. Moreover, SHAtropE also provides the predicted ZTD uncertainty, which is valuable in Precise Point Positioning (PPP) with ZTD being constrained for faster convergence. The data of 310 GNSS sites over 7 years were used to validate the new model. Results show that the SHAtropE ZTD has an accuracy of 3.5 cm in root mean square (RMS) quantity, which has a mean improvement of 35.2% and 5.4% over the UNB3m (5.4 cm) and GPT3 (3.7 cm) models, respectively. The predicted uncertainty of SHAtropE ZTD shows seasonal variations, where the values are larger in summer than in winter. By applying the SHAtropE model in the static PPP, the convergence time of GPS-only and BDS-only solutions are reduced by 8.1% and 14.5% respectively compared to the UNB3m model, and the reductions are 6.9% and 11.2% respectively for the GPT3 model. As no meteorological data are required for the implementation of the model, the SHAtropE could thus be a refined tropospheric model for GNSS users in mainland China and the surrounding areas. The method of modeling the ZTD uncertainty can also be used in further global tropospheric delay modeling.

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