Efficiency of updating the ionospheric models using total electron content at mid- and sub-auroral latitudes

GPS Solutions ◽  
2019 ◽  
Vol 24 (1) ◽  
Author(s):  
Daria S. Kotova ◽  
Vladimir B. Ovodenko ◽  
Yury V. Yasyukevich ◽  
Maxim V. Klimenko ◽  
Konstantin G. Ratovsky ◽  
...  
Keyword(s):  
Total Electron Content ◽  
Electron Content ◽  
Total Electron ◽  
Ionospheric Models

scholarly journals Global Ionospheric Model Accuracy Analysis Using Shipborne Kinematic GPS Data in the Arctic Circle

2019 ◽  
Vol 11 (17) ◽  
pp. 2062
Author(s):  
Di Wang ◽  
Xiaowen Luo ◽  
Jinling Wang ◽  
Jinyao Gao ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Total Electron Content ◽  
Satellite System ◽  
The Arctic ◽  
Electron Content ◽  
Ionospheric Model ◽  
International Gnss Service ◽  
Total Electron ◽  
Arctic Circle ◽  
Analysis And Evaluation ◽  
Ionospheric Models

The global ionospheric model built by the International Global Navigation Satellite System (GNSS) Service (IGS) using GNSS reference stations all over the world is currently the most widely used ionospheric product on a global scale. Therefore, analysis and evaluation of this ionospheric product’s accuracy and reliability are essential for the practical use of the product. In contrast to the traditional way of assessing global ionospheric models with ground-based static measurements, our study used shipborne kinematic global positioning system (GPS) measurements collected over 18 days to perform a preliminary analysis and evaluation of the accuracy of the global ionospheric models; our study took place in the Arctic Circle. The data from the International GNSS Service stations near the Arctic Circle were used to verify the ionospheric total electron contents derived from the kinematic data. The results suggested that the global ionospheric model had an approximate regional accuracy of 12 total electron content units (TECu) within the Arctic Circle and deviated from the actual ionospheric total electron content value by about 4 TECu.

Comparative analysis of global ionospheric models used in GNSS data processing based on selected stations

2021 ◽  
Author(s):  
Paulina Woźniak ◽  
Anna Świątek ◽  
Leszek Jaworski
Keyword(s):  
Total Electron Content ◽  
Satellite System ◽  
Ionospheric Delay ◽  
Satellite Orbits ◽  
Electron Content ◽  
Free Electrons ◽  
Total Electron ◽  
Ionospheric Models ◽  
Station Coordinates ◽  
The Difference

<p>Among the many error sources affecting GNSS <em>(Global Navigation Satellite System)</em> positioning accuracy, the ionosphere is the cause of those of the greatest value. The ionized gas layer, where also free electrons are present, extends from the upper atmosphere to 1,000 km above the Earth's surface (conventionally). As the GNSS satellite orbits altitude is more than 20,000 km, the wave transmitted from the satellite to the receiver on the Earth’s ground passes through this layer, but not unscathed. The ionosphere is a dispersive medium for the electromagnetic waves in the microwave band, including UHF <em>(Ultra High Frequency)</em> waves transmitted by GNSS satellites. As a result, the group velocity of the wave decreases, while its phase velocity – increases.</p><p>Ionospheric delay compensation methods include among others multi-frequency measurements;  however, when considering measurements on one frequency, the usage of ionospheric models is an option. The key element is the number of free electrons, its inclusion in the course of calculations is possible thanks to the TEC <em>(Total Electron Content)</em> maps. Taking into account the variability of the coefficient in the daily and annual course, as well as depending on the activity of the Sun and its 11-year cycle, it is important to use the current value for a given place and time.</p><p>For the European Galileo satellite system a dedicated ionospheric model NeQuick-G was developed. As a simple modification of the formula allows it to be applied to other satellite systems, it can be considered in a broader context, regardless of the system and receiver location. In our study the TEC maps published by IGS are used as the comparative data. As a reference, the station located in Warsaw, Poland, is adopted.</p><p>The subject of this research is the reliability and validity of the model in equatorial region. The analysis is performed for the stations belonging to the IGS <em>(International GNSS Service)</em> network, located in the discussed area. For each hour of the day, independently for each month of 2019, statistic parameters are determined for both models as well as for the difference between them. The results are analysed taking into account the local time of individual stations. The decisive element is the comparison of the station position time series during disturbed and quiet ionospheric conditions (selected based on the K-index), using each of the models (single-frequency observations). The station coordinates are determined from GPS <em>(Global Positioning System)</em> data using the PPP <em>(Precise Point Positioning)</em> method; the position determined for the iono-free combination (dual-frequency observations) is used as a reference.</p><p>The ionospheric delay is directly proportional to the value of the TEC parameter. The difference between the models, exceeding on average even 20 TECU <em>(Total Electron Content Unit)</em> during some periods, translates into a station coordinate differences. The presented analysis may indicate the need for local improvement of global ionospheric models in the discussed region, which will consequently affect the GNSS positioning quality.</p>

Evaluation of six ionospheric models as predictors of total electron content

Radio Science ◽  
1991 ◽  
Vol 26 (4) ◽  
pp. 1007-1015 ◽  
Author(s):  
Lincoln D. Brown ◽  
Robert E. Daniell ◽  
Matthew W. Fox ◽  
John A. Klobuchar ◽  
Patricia H. Doherty
Keyword(s):  
Total Electron Content ◽  
Electron Content ◽  
Total Electron ◽  
Ionospheric Models

scholarly journals Comparison of quite time ionospheric total electron content from IRI-2016 model and GPS observations

2019 ◽  
Author(s):  
Mulugeta Melaku ◽  
Gizaw Mengistu Tsidu
Keyword(s):  
Total Electron Content ◽  
Extreme Values ◽  
Probability Of Detection ◽  
Electron Content ◽  
Polar Regions ◽  
Total Electron ◽  
Gps Tec ◽  
Ionospheric Models ◽  
Spatio Temporal ◽  
Set Up

Abstract. Earth's ionosphere is an important medium of radio wave propagation in modern times. However, the effective use of ionosphere depends on the understanding of its spatio-temporal variability. Towards this end, a number of ground and space-based monitoring facilities have been set up over the years. This is also complemented by model-based studies. However, assessment of the performance of the ionospheric models in capturing observations needs to be conducted. In this work, the performance of IRI-2016 model in simulating total electron content (TEC) observed by network of global position System (GPS) is evaluated based on RMSE, bias, correlation and categorical metrics such as Quantile Probability of Detection (QPOD), Quantile False Alarm Ratio (QFAR), Quantile Categorical Miss (QCM), and Quantile Critical Success Index(QCSI). IRI-2016 model simulations are evaluated against GPS-TEC observations during the solar minima 2008 and maxima 2013. Higher correlation, low RMSE and bias between the modeled and measured TEC values are observed during solar minima than solar maxima. The IRI-2016 model TEC agrees with GPS-TEC strongly over higher latitudes than over tropics in general and EIA crest regions in particular as demonstrated by low RMSE and bias. However, the phases of modeled and simulated TEC agree strongly over the rest of the globe with the exception of the polar regions as indicated by high correlation during all solar activities. Moreover, the performance of the model in capturing extreme values over magnetic equator, mid- and high-latitudes is poor. This has been noted from a decrease in QPOD, QCSI and an increase in QCM and QFAR over most of the globe with an increase in the threshold percentile values of TEC to be simulated from 10 % to 90 % during both solar minimum and maximum periods. The performance of IRI-2016 in correctly simulating observed low (as low as 10th percentile) and high (high than 90th percentile) TEC over EIA crest regions is reasonably good given that IRI-2016 is a climatological model despite large RMSE and positive model bias. Therefore, this study reveals the strength of the IRI-2016 model, which was concealed due to large RMSE and positive bias, in correctly simulating the observed TEC distribution during all seasons and solar activities for the first time. However, it is also worth noting that the performance of IRI-2016 model is relatively poor in 2013 compared to that of 2008 at the higher ends of the TEC distribution.

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