A comprehensive comparison of atmospheric mapping functions for GPS measurements in Egypt

AbstractThe principal limiting error source in the Global Positioning System (GPS) is the mismodeling of the delay experienced by radio waves in propagating through the atmosphere. The atmosphere causing the delay in GPS signals consists of two main layers: the ionosphere and the troposphere. The ionospheric delay can be mitigated using dual frequency receivers, but the tropospheric delay is often corrected using a standard tropospheric model. The tropospheric delay can be described as a product of the delay at the zenith and a mapping function, which models the elevation dependence of the propagation delay. A large number of mapping functions have been developed for use in the analysis of space geodetic data. An assessment of most of these mapping functions including those developed by Niell (NMF), Herring (MTT), Davis (CfA-2.2), Ifadis, Chao, Black & Eisner (B & E), Yang & Ping, Moffett, Vienna (VMF), and Isobaric (IMF) have been performed. The behavior of these mapping functions was assessed by comparing their results with highly accurate Numerical Integration based Models (NIM) for three different stations in Egypt (Aswan, Helwan, and Mersa Matrouh) at different times throughout the year. The meteorological data used in this study was taken from the Egyptian Meteorological Authority (EMA) as average values between 1990 and 2005. It can be concluded that the Black & Eisner mapping function is recommended for dry tropospheric delay prediction for low zenith angles, whereas VMF will be the choice for elevation angles up to 10°.

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Evaluation of Wet Mapping Functions Used in Modeling Tropospheric Propagation Delay Effect on GPS Measurements

The Open Atmospheric Science Journal ◽

10.2174/1874282301711010001 ◽

2017 ◽

Vol 11 (1) ◽

pp. 1-15 ◽

Cited By ~ 1

Author(s):

Sobhy Abdel-Monam Younes

Keyword(s):

A Priori ◽

Mapping Function ◽

Propagation Delay ◽

Radiosonde Data ◽

Tropospheric Delay ◽

Delay Effect ◽

Gps Measurements ◽

Mapping Functions ◽

Significant Bias ◽

Mapping Techniques

Background:The author compares several methods to map the a priori wet tropospheric delay of GNSS signals in Egypt from the zenith direction to lower elevations.Methods and Materials:The author compared the following mapping techniques against ray-traced delays computed for radiosonde profiles under the assumption of spherical symmetry: Saastamoinen, Hopfield, Black, Chao, Ifadis, Herring, Niell, Moffett, Black and Eisner and UNBabc mapping functions. Radiosonde data were computed from radiosonde stations at the Egyptian stations; in the south of Egypt, near the Mediterranean Sea, and near the Red Sea over a period of 5 years (2000-2005), most of the stations launched radiosonde twice daily, every day of the year. Moreover, data is received from the Egyptian Meteorology Authority.Results and Conclusion:The results indicate that currently, the saastamoinen mapping function should be used for all geodetic applications in Egypt, and if necessary, the Chao and Moffett mapping functions can serve as an acceptable replacement without introducing a significant bias into the station position.

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Single station GNSS tomography as a replacement of mapping function for high precision troposphere radio wave delay correction

10.5194/egusphere-egu2020-12133 ◽

2020 ◽

Author(s):

Feng Peng ◽

Li Fei ◽

Jean-Pierre Barriot ◽

Yan Jianguo ◽

Zhang Fangzhao ◽

...

Keyword(s):

Radio Wave ◽

Time Resolution ◽

Mapping Function ◽

Satellite Tracking ◽

Tropospheric Delay ◽

High Time Resolution ◽

Signal Delay ◽

Mapping Functions ◽

Single Station ◽

Delay Correction

With its relatively low cost, high availability and continuous observation ability, zenith delays from GPS combined with mapping function have been used in satellite tracking media calibration since early 2000. The mapping functions are used to model elevation dependency of radio wave delays in the troposphere. It assumes that the ratio of signal slant delay over zenith delay is less variable w.r.t time and location than the signal delay itself. Thus the parameters of signal delay elevation dependency can be modeled and unknowns of the tropospheric delay were reduced. However, the parameterization comes with a loss of accuracy. For example, the state-of-art VMF series mapping functions have a time resolution of 6 hours, which means variations that took place in less than 6 hours are smoothed. Nowadays GPS has evolved to multi-constellation GNSS with many more satellites in visibility. Here we propose a single station GNSS tomography algorithm for radio wave delay correction by directly using slant delays. This algorithm can extract the information of the troposphere variations in all the signal directions of GNSS observations with high time resolution. Thus it will be beneficial to the radio wave delay correction of precise satellite tracking. We assess the performance of this algorithm with a collocated water vapor radiometer.

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Evaluation of Symmetric Neutral-Atmosphere Mapping Functions Using Ray-Tracing Through Radiosonde Observations

Artificial Satellites ◽

10.2478/arsa-2013-0015 ◽

2013 ◽

Vol 48 (4) ◽

pp. 171-189

Author(s):

A.H. Souri ◽

M.A. Sharifi

Keyword(s):

Ray Tracing ◽

Elevation Angle ◽

Mapping Function ◽

Ground Truth ◽

Ease Of Use ◽

Tropospheric Delay ◽

Neutral Atmosphere ◽

Mapping Functions ◽

Climatic Regions ◽

Online Mapping

Abstract The aim of this paper is to compare the validity of six recent symmetric mapping functions. The mapping function models the elevation angle dependence of the tropospheric delay. Niell Mapping Function (NMF), Vienna Mapping Function (VMF1), University of New Brunswick- VMF1 (UNB-VMF1) mapping functions, Global Mapping Function (GMF) and Global Pressure and Temperature (GPT2)/GMF are evaluated by using ray tracing through 25 radiosonde stations covering different climatic regions in one year. The ray-traced measurements are regarded as “ground truth”. The ray-tracing approach is performed for diverse elevation angle starting at 5° to 15°. The results for both hydrostatic and non-hydrostatic components of mapping functions support the efficiency of online-mapping functions. The latitudinal dependence of standard deviation for 5° is also demonstrated. Although all the tested mapping functions can provide satisfactory results when used for elevation angles above 15°, for high precision geodetic measurements, it is highly recommended that the online-mapping functions (UNBs and VMF1) be used.The results suggest that UNB models, like VMF have strengths and weaknesses and do not stand out as being consistently better or worse than the VMF1. The GPT2/GMF provided better accuracy than GMF and NMF. Since all of them do not require site specific data; therefore GPT2/GMF can be useful as regards its ease of use.

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The Effect of the State-of-the-Art Mapping Functions on Precise Point Positioning

10.5194/egusphere-egu2020-443 ◽

2020 ◽

Author(s):

Faruk Can Durmus ◽

Bahattin Erdogan

Keyword(s):

Water Vapor ◽

Precise Point Positioning ◽

State Of The Art ◽

Mapping Function ◽

Empirical Models ◽

Global Navigation Satellite Systems ◽

Tropospheric Delay ◽

Positioning Accuracy ◽

Mapping Functions ◽

Point Positioning

Global Navigation Satellite Systems (GNSS) are effectively used for different applications of Geomatic Engineering. There are lots of model error sources that affect the performance of the point positioning. Especially for the Precise Point Positioning (PPP) technique, which depends on the absolute point positioning, these errors should be modelled since PPP technique utilizes un-differenced and ionosphere-free combinations. Studies about PPP technique show that the effect of tropospheric delay caused by water vapor and dry air in the troposphere, which affects GNSS signals, is an important parameter should be modelled. Total zenith delay consists of both hydrostatic and wet delay. Hydrostatic delay can be accurately estimated by using atmospheric surface pressure and temperature with empirical models. Although there are many empirical models currently used for the determination of the zenith wet delay, the accuracies of these models are inadequate due to the temporal and spatial variation of atmospheric water vapor. Moreover, the tropospheric delay occurs along the path of GNSS signals and the Mapping Functions (MFs) are used to convert the tropospheric signal delay along the zenith direction to the slant direction. In this study, it is aimed to measure the effect of the globally produced MFs as Niell Mapping Function (NMF), Vienna Mapping Function 1 (VMF1), Global Mapping Function (GMF) and Global Pressure Temperature model 2 (GPT2) for GNSS positioning accuracy. Only GPS satellite system has been taken into account. For the analysis it has planned to process approximately 294 permanent stations from Crustal Dynamics Data Information System (CDDIS) archive with Jet Propulsion Laboratory&#8217;s GipsyX v1.2 software. In order to reveal the effect of different season the GPS observations in January, April, July and October, 2018 have been obtained. The solutions were derived for different session durations as 2, 4, 6, 8, 12 and 24 hours for each global MFs and root mean square values have been estimated for each session durations. According to the first results that based on the six points, which the ellipsoidal heights of them are between 20 m and 105 m, although the results of north and east components are close to each other; the results of VMF1 are better than other global MFs for up component.&#160;Keywords: State-of-the-Art Mapping Function, Troposphere, Precise Point Positioning, Accuracy, GipsyX

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Comparative analysis of blind tropospheric correction models in Ghana

Journal of Geodetic Science ◽

10.1515/jogs-2020-0104 ◽

2021 ◽

Vol 11 (1) ◽

pp. 14-26

Author(s):

S. Osah ◽

A. A. Acheampong ◽

C. Fosu ◽

I. Dadzie

Keyword(s):

Prediction Models ◽

Mapping Function ◽

Satellite System ◽

Tropospheric Delay ◽

Model Bias ◽

Significance Level ◽

Significant Difference ◽

Global Navigation Satellite ◽

The Impact ◽

Delay Prediction

Abstract The impact of the earth’s atmospheric layers, particularly the troposphere on Global Navigation satellite system (GNSS) signals has become a major concern in GNSS accurate positioning, navigation, surveillance and timing applications. For precise GNSS applications, tropospheric delay has to be mitigated as accurately as possible using tropospheric delay prediction models. However, the choice of a particular prediction model can signifi-cantly impair the positioning accuracy particularly when the model does not suit the user’s environment. A performance assessment of these prediction models for a suitable one is very important. In this paper, an assessment study of the performances of five blind tropospheric delay prediction models, the UNB3m, EGNOS, GTrop, GPT2w and GPT3 models was conducted in Ghana over six selected Continuously Operating Reference Stations (CORS) using the 1˚x1˚ gridded Vienna Mapping Function 3 (VMF3) zenith tropospheric delay (ZTD) product as a reference. The gridded VMF3-ZTD which is generated for every six hours on the 1˚x1˚ grids was bilinearly interpolated both space and time and transferred from the grid heights to the respective heights of the CORS locations. The results show that the GPT3 model performed better in estimating the ZTD with an overall mean (bias: 2.05 cm; RMS: 2.53 cm), followed by GPT2w model (bias: 2.32cm; RMS: 2.76cm) and GTrop model (bias: 2.41cm; 2.82cm). UNB3m model (bias: 6.23 cm; RMS: 6.43 cm) and EGNOS model (bias: 6.70 cm; RMS: 6.89 cm) performed poorly. A multiple comparison test (MCT) was further performed on the RMSE of each model to check if there is significant difference at 5% significant level. The results show that the GPT3, GPT2w and GTrop models are significantly indifferent at 5% significance level indicating that either of these models can be employed to mitigate the ZTD in the study area, nevertheless, the choice of GPT3 model will be more preferable.

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Using Different Mapping Function In GPS Processing For Remote Sensing The Atmosphere

Journal of Applied Engineering Sciences ◽

10.1515/jaes-2015-0024 ◽

2015 ◽

Vol 5 (2) ◽

pp. 73-80 ◽

Cited By ~ 1

Author(s):

S. Nistor ◽

A.S. Buda

Keyword(s):

Mapping Function ◽

Order Effect ◽

Tropospheric Delay ◽

Mapping Functions ◽

Zenith Tropospheric Delay ◽

Zenith Wet Delay ◽

Different Types ◽

Gps Processing ◽

Zenith Hydrostatic Delay ◽

L1 And L2

Abstract Due to development of GPS technology and by using the combination LC of L1 and L2 frequency the first order effect of the ionosphere tends to be canceled. Thus the main source of errors in the atmosphere which causes the delay in GPS signal is the neutral part of the atmosphere, usually referred to tropospheric delay. In general, the delay is computed at the zenith direction and it is referred to zenith tropospheric delay. The zenith tropospheric delay consist of two parts: zenith hydrostatic delay and zenith wet delay. The zenith hydrostatic delay can be very well modeled which accounts for nearly 90% to 100% of the atmospheric delay. The zenith wet delay is due to the water vapor and represents the “harder” part that need to be modeled caused by “unmixed” condition of the wet atmosphere. The influence of the zenith wet delay is around 0-40 cm. The aim of the article is to present the results obtain on the network of three station which were spread around the Oradea city using different types of mapping functions. The mapping functions are: global pressure and temperature – GPT2 and Vienna mapping function – VMF1. For the vertical studies to obtain the highest accuracy, the recommended mapping function is VMF1.

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

Remote Sensing ◽

10.3390/rs12010165 ◽

2020 ◽

Vol 12 (1) ◽

pp. 165 ◽

Cited By ~ 3

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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The Performance of Different Mapping Functions and Gradient Models in the Determination of Slant Tropospheric Delay

Remote Sensing ◽

10.3390/rs12010130 ◽

2020 ◽

Vol 12 (1) ◽

pp. 130 ◽

Cited By ~ 1

Author(s):

Cong Qiu ◽

Xiaoming Wang ◽

Zishen Li ◽

Shaotian Zhang ◽

Haobo Li ◽

...

Keyword(s):

Mapping Function ◽

Temperate Zone ◽

Global Navigation Satellite Systems ◽

Tibet Plateau ◽

Tropospheric Delay ◽

Mapping Functions ◽

Satellite Systems ◽

Bending Effect ◽

Gradient Models

Global navigation satellite systems (GNSSs) have become an important tool for remotely sensing water vapor in the atmosphere. In GNSS data processing, mapping functions and gradient models are needed to map the zenith tropospheric delay (ZTD) to the slant total tropospheric delay (STD) along a signal path. Therefore, it is essential to investigate the spatial–temporal performance of various mapping functions and gradient models in the determination of STD. In this study, the STDs at nine elevations were first calculated by applying the ray-tracing method to the atmospheric European Reanalysis-Interim (ERA—Interim) dataset. These STDs were then used as the reference to study the accuracy of the STDs that determined the ZTD together with mapping functions and gradient models. The performance of three mapping functions (i.e., Niell mapping function (NMF), global mapping function (GMF), and Vienna mapping function (VMF1)) and three gradient models (i.e., Chen, MacMillan, and Meindl) in six regions (the temperate zone, Qinghai–Tibet Plateau, Equator, Sahara Desert, Amazon Rainforest, and North Pole) in determining slant tropospheric delay was investigated in this study. The results indicate that the three mapping functions have relatively similar performance above a 15° elevation, but below a 15° elevation, VMF1 clearly performed better than the GMF and NMF. The results also show that, if no gradient model is included, the root-mean-square (RMS) of the STD is smaller than 2 mm above the 30° elevation and smaller than 9 mm above the 15° elevation but shows a significant increase below the 15° elevation. For example, in the temperate zone, the RMS increases from approximately 35 mm at the 10° elevation to approximately 160 mm at the 3° elevation. The inclusion of gradient models can significantly improve the accuracy of STDs by 50%. All three gradient models performed similarly at all elevations and in all regions. The bending effect was also investigated, and the results indicate that the tropospheric delay caused by the bending effect is normally below 13 mm above a 15° elevation, but this delay increases dramatically from approximately 40 mm at a 10° elevation to approximately 200 mm at a 5° elevation, and even reaches 500–700 mm at a 3° elevation in most studied regions.

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Symmetric Neutral-Atmosphere Mapping Functions: A Review of the State-Of-The-Art

Artificial Satellites ◽

10.2478/arsa-2013-0014 ◽

2013 ◽

Vol 48 (4) ◽

pp. 159-170 ◽

Cited By ~ 1

Author(s):

M.A. Sharifi ◽

A.H. Souri

Keyword(s):

State Of The Art ◽

Elevation Angle ◽

Mapping Function ◽

Temporal Variations ◽

Neutral Atmosphere ◽

Radio Waves ◽

Mapping Functions ◽

Long Baseline ◽

Global Mapping ◽

Spatio Temporal

ABSTRACT The aim of this paper is to review of six recent symmetric mapping functions. The mapping function can be largely used for GPS meteorological measurements, InSAR atmospheric corrections and precise measurements of very long baseline interferometry (VLBI). These spacebased techniques use radio signal that propagate through the Earth's atmosphere. The electrically-neutral region, predominantly the troposphere, affects the speed and direction of travel of radio waves leading to existence of excess path. The mapping function models the elevation angle dependence of the delay. Within the past decade, significant improvements have been achieved in order to use of Numerical Weather Models (NWM) for geodetic positioning. Ray-tracing algorithms have been performed through refractivity shells retrieved from NWMs in order to relate zenith delays to slant delays. Therefore, there seems to be a real need for deep review of recent developments in the mapping function domain. This paper proposes a comprehensive review of the symmetric mapping functions state of the art, their spatio-temporal variations and used NWM and generic models. Niell Mapping Function (NMF), Vienna Mapping Function (VMF1), University of New Brunswick-VMF1 (UNB-VMF1) mapping functions, Global Mapping Function (GMF) and Global Pressure and Temperature (GPT2)/GMF are reviewed in this paper.

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The Effect of the State-of-the-Art Mapping Functions on Precise Point Positioning

10.5194/egusphere-egu21-9976 ◽

2021 ◽

Author(s):

Faruk Can Durmus ◽

Bahattin Erdogan

Keyword(s):

Water Vapor ◽

Precise Point Positioning ◽

State Of The Art ◽

Mapping Function ◽

Empirical Models ◽

Global Navigation Satellite Systems ◽

Tropospheric Delay ◽

Positioning Accuracy ◽

Mapping Functions ◽

Point Positioning

Global Navigation Satellite Systems (GNSS) are effectively used for different applications of Geomatic Engineering. There are lots of model error sources that affect the performance of the point positioning. Especially for the Precise Point Positioning (PPP) technique, which depends on the absolute point positioning, these errors should be modelled since PPP technique utilizes un-differenced and ionosphere-free combinations. Studies about PPP technique show that the effect of tropospheric delay caused by water vapor and dry air in the troposphere, which affects GNSS signals, is an important parameter should be modelled. Total zenith delay consists of both hydrostatic and wet delay. Hydrostatic delay can be accurately estimated by using atmospheric surface pressure and height with empirical models. Although there are many empirical models currently used for the determination of the zenith wet delay, the accuracies of these models are inadequate due to the temporal and spatial variation of atmospheric water vapor. Moreover, the tropospheric delay occurs along the path of GNSS signals and the Mapping Functions (MFs) are used to convert the tropospheric signal delay along the zenith direction to the slant direction. In this study, it is aimed to measure the effect of the globally produced MFs as Niell Mapping Function (NMF), Vienna Mapping Function 1 (VMF1), Global Mapping Function (GMF) and Global Pressure Temperature model 2 (GPT2) for GNSS positioning accuracy. Only GPS satellite system has been taken into account. For the analysis it has planned to process approximately 294 permanent stations from Crustal Dynamics Data Information System (CDDIS) archive with Jet Propulsion Laboratory&#8217;s GipsyX v1.2 software. In order to reveal the effect of different season the GPS observations in January, April, July and October, 2018 have been obtained. The solutions were derived for different session durations as 2, 4, 6, 8, 12 and 24 hours for each global MFs and root mean square values have been estimated for each session durations.Keywords: State-of-the-Art Mapping Function, Troposphere, Precise Point Positioning, Accuracy, GipsyX

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