scholarly journals A New Global Total Electron Content Empirical Model

2019 ◽  
Vol 11 (6) ◽  
pp. 706 ◽  
Author(s):  
Jiandi Feng ◽  
Baomin Han ◽  
Zhenzhen Zhao ◽  
Zhengtao Wang
Keyword(s):  
Total Electron Content ◽  
Empirical Model ◽  
Single Point ◽  
Empirical Models ◽  
Electron Content ◽  
International Gnss Service ◽  
Prediction Ability ◽  
Total Electron ◽  
Grid Model ◽  
Grid Points

Research on total electron content (TEC) empirical models is one of the important topics in the field of space weather services. Global TEC empirical models based on Global Ionospheric Maps (GIMs) TEC data released by the International GNSS Service (IGS) have developed rapidly in recent years. However, the accuracy of such global empirical models has a crucial restriction arising from the non-uniform accuracy of IGS TEC data in the global scope. Specifically, IGS TEC data accuracy is higher on land and lower over the ocean due to the lack of stations in the latter. Using uneven precision GIMs TEC data as a whole for model fitting is unreasonable. Aiming at the limitation of global ionospheric TEC modelling, this paper proposes a new global ionospheric TEC empirical model named the TECM-GRID model. The model consists of 5183 sections, corresponding to 5183 grid points (longitude 5°, latitude 2.5°) of GIM. Two kinds of single point empirical TEC models, SSM-T1 and SSM-T2, are used for TECM-GRID. According to the locations of grid points, the SSM-T2 model is selected as the sub-model in the Mid-Latitude Summer Night Anomaly (MSNA) region, and SSM-T1 is selected as the sub-model in other regions. The fitting ability of the TECM-GRID model for modelling data was tested in accordance with root mean square (RMS) and relative RMS values. Then, the TECM-GRID model was validated and compared with the NTCM-GL model and Center for Orbit Determination in Europe (CODE) GIMs at time points other than modelling time. Results show that TECM-GRID can effectively describe the Equatorial Ionization Anomaly (EIA) and the MSNA phenomena of the ionosphere, which puts it in good agreement with CODE GIMs and means that it has better prediction ability than the NTCM-GL model.

scholarly journals Neural network based model for global Total Electron Content forecasting

2020 ◽  
Vol 10 ◽  
pp. 11 ◽  
Author(s):  
Claudio Cesaroni ◽  
Luca Spogli ◽  
Angela Aragon-Angel ◽  
Michele Fiocca ◽  
Varuliator Dear ◽  
...  
Keyword(s):  
Neural Network ◽  
Total Electron Content ◽  
Geomagnetic Storms ◽  
Single Point ◽  
Global Scale ◽  
External Input ◽  
Electron Content ◽  
International Gnss Service ◽  
Total Electron ◽  
Grid Points

We introduce a novel empirical model to forecast, 24 h in advance, the Total Electron Content (TEC) at global scale. The technique leverages on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and applies a nonlinear autoregressive neural network with external input (NARX) to selected GIM grid points for the 24 h single-point TEC forecasting, taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a global scale, the technique makes use of the NeQuick2 Model fed by an effective sunspot number R12 (R12eff), estimated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same GIM grid points. The novel approach is able to reproduce the features of the ionosphere especially during disturbed periods. The performance of the forecasting approach is extensively tested under different geospatial conditions, against both TEC maps products by UPC (Universitat Politècnica de Catalunya) and independent TEC data from Jason-3 spacecraft. The testing results are very satisfactory in terms of RMSE, as it has been found to range between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-h forecasting technique even over the oceans. The validation of the forecasting during five geomagnetic storms reveals that the model performance is not deteriorated during disturbed periods. This 24-h empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to support different classes of GNSS users.

scholarly journals IONORING: Real-Time Monitoring of the Total Electron Content over Italy

2021 ◽  
Vol 13 (16) ◽  
pp. 3290
Author(s):  
Claudio Cesaroni ◽  
Luca Spogli ◽  
Giorgiana De Franceschi
Keyword(s):  
Real Time ◽  
Total Electron Content ◽  
Geomagnetic Storms ◽  
Single Point ◽  
Satellite System ◽  
Electron Content ◽  
Real Time Monitoring ◽  
International Gnss Service ◽  
Total Electron ◽  
Global Navigation Satellite

IONORING (IONOspheric RING) is a tool capable to provide the real-time monitoring and modeling of the ionospheric Total Electron Content (TEC) over Italy, in the latitudinal and longitudinal ranges of 35°N-48°N and 5°E-20°E, respectively. IONORING exploits the Global Navigation Satellite System (GNSS) data acquired by the RING (Rete Integrata Nazionale GNSS) network, managed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The system provides TEC real-time maps with a very fine spatial resolution (0.1° latitude x 0.1° longitude), with a refresh time of 10 min and a typical latency below the minute. The TEC estimated at the ionospheric piercing points from about 40 RING stations, equally distributed over the Italian territory, are interpolated using locally (weighted) regression scatter plot smoothing (LOWESS). The validation is performed by comparing the IONORING TEC maps (in real-time) with independent products: i) the Global Ionospheric Maps (GIM) - final product- provided by the International GNSS Service (IGS), and ii) the European TEC maps from the Royal Observatory of Belgium. The validation results are satisfactory in terms of Root Mean Square Error (RMSE) between 2 and 3 TECu for both comparisons. The potential of IONORING in depicting the TEC daily and seasonal variations is analyzed over 3 years, from May 2017 to April 2020, as well as its capability to account for the effect of the disturbed geospace on the ionosphere at mid-latitudes. The IONORING response to the X9.3 flare event of September 2017 highlights a sudden TEC increase over Italy of about 20%, with a small, expected dependence on the latitude, i.e., on the distance from the subsolar point. Subsequent large regional TEC various were observed in response to related follow-on geomagnetic storms. This storm is also used as a case event to demonstrate the potential of IONORING in improving the accuracy of the GNSS Single Point Positioning. By processing data in kinematic mode and by using the Klobuchar as the model to provide the ionospheric correction, the resulting Horizontal Positioning Error is 4.3 m, lowering to, 3.84 m when GIM maps are used. If IONORING maps are used as the reference ionosphere, the error is as low as 2.5 m. Real-times application and services in which IONORING is currently integrated are also described in the conclusive remarks.

A new regional total electron content empirical model in northeast China

2016 ◽  
Vol 58 (7) ◽  
pp. 1155-1167 ◽  
Author(s):  
Jiandi Feng ◽  
Zhengtao Wang ◽  
Weiping Jiang ◽  
Zhenzhen Zhao ◽  
Bingbing Zhang
Keyword(s):  
Total Electron Content ◽  
Empirical Model ◽  
Northeast China ◽  
Electron Content ◽  
Total Electron

scholarly journals An empirical model of ionospheric total electron content (TEC) near the crest of the equatorial ionization anomaly (EIA)

2016 ◽  
Vol 6 ◽  
pp. A29 ◽  
Author(s):  
Rajkumar Hajra ◽  
Shyamal Kumar Chakraborty ◽  
Bruce T. Tsurutani ◽  
Ashish DasGupta ◽  
Ezequiel Echer ◽  
...  
Keyword(s):  
Total Electron Content ◽  
Empirical Model ◽  
Electron Content ◽  
Total Electron ◽  
Ionospheric Total Electron Content ◽  
Equatorial Ionization Anomaly

scholarly journals Redes neurais artificiais aplicadas na previsão do VTEC no Brasil

2013 ◽  
Vol 19 (2) ◽  
pp. 227-246 ◽  
Author(s):  
Wagner Carrupt Machado ◽  
Edvaldo Simões da Fonseca Junior
Keyword(s):  
Total Electron Content ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
International Gnss Service ◽  
Total Electron ◽  
De Se ◽  
Pierce Point ◽  
Global Ionospheric Maps

Uma forma de se prever o conteúdo total de elétrons na direção vertical (VTEC - Vertical Total Electron Content) usando a arquitetura de redes neurais artificiais (RNA) denominada de perceptrons de múltiplas camadas (MLP - MultipLayer Percetrons) é apresentada e avaliada nesta pesquisa. As entradas do modelo foram definidas como sendo a posição dos pontos ionosféricos (IPP - Ionospheric Pierce Point) e o tempo universal (TU), enquanto que a saída é o VTEC. As variações sazonais e de períodos mais longos são levadas em conta através da atualização do treinamento diariamente. Testes foram conduzidos sobre uma área que abrange o Brasil e sua vizinhança considerando períodos de alta e baixa atividade solar. As RNA foram treinadas utilizando informações dos mapas globais da ionosfera (GIM - Global Ionospheric Maps) produzidos pelo serviço internacional do GNSS (IGS - International GNSS Service) das 72 horas anteriores à época de início da previsão. As RNA treinadas foram utilizadas para prever o VTEC por 72 horas (VTEC RNA). Os VTEC RNA foram comparados com os VTEC contidos nos GIM (VTEC GIM). A raiz do erro médio quadrático (RMS) da diferença entre o VTEC GIM e o VTEC RNA variou de 1,4 a 10,7 unidades de TEC (TECU). O erro relativo mostra que a RNA proposta foi capaz de prever o VTEC com 70 a 85% de acerto.

scholarly journals Single point positioning with vertical total electron content estimation based on single-epoch data

2021 ◽  
Vol 10 (1) ◽  
pp. 1-12
Author(s):  
Artur Fischer ◽  
Sławomir Cellmer ◽  
Krzysztof Nowel
Keyword(s):  
Total Electron Content ◽  
Single Point ◽  
Error Reduction ◽  
Ionospheric Delay ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Total Electron ◽  
Single Point Positioning ◽  
External Data ◽  
Point Positioning

Abstract. This paper proposes a new mathematical method of ionospheric delay estimation in single point positioning (SPP) using a single-frequency receiver. The proposed approach focuses on the Δ vertical total electron content (VTEC) component estimation (MSPPwithdVTEC) with the assumption of an initial and constant value equal to 5 TECU in any observed epoch. The principal purpose of the study is to examine the reliability of this approach to become independent from the external data in the ionospheric correction calculation process. To verify the MSPPwithdVTEC, the SPP with the Klobuchar algorithm was employed as a reference model, utilizing the coefficients from the navigation message. Moreover, to specify the level of precision of the MSPPwithdVTEC, the SPP with the International Global Navigation Satellite Systems (GNSS) Service (IGS) TEC map was adopted for comparison as the high-quality product in the ionospheric delay determination. To perform the computational tests, real code data were involved from three different localizations in Scandinavia using two parallel days. The criterion was the ionospheric changes depending on geodetic latitude. Referring to the Klobuchar model, the MSPPwithdVTEC obtained a significant improvement of 15 %–25 % in the final SPP solutions. For the SPP approach employing the IGS TEC map and for the MSPPwithdVTEC, the difference in error reduction was not significant, and it did not exceed 1.0 % for the IGS TEC map. Therefore, the MSPPwithdVTEC can be assessed as an accurate SPP method based on error reduction value, close to the SPP approach with the IGS TEC map. The main advantage of the proposed approach is that it does not need external data.

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.

scholarly journals Regional reference total electron content model over Japan based on neural network mapping techniques

2007 ◽  
Vol 25 (12) ◽  
pp. 2609-2614 ◽  
Author(s):  
T. Maruyama
Keyword(s):  
Neural Network ◽  
Solar Activity ◽  
Total Electron Content ◽  
Reference Model ◽  
Activity Period ◽  
Electron Content ◽  
Total Electron ◽  
Grid Points ◽  
Using Data ◽  
Regional Reference

Abstract. A regional reference model of total electron content (TEC) was constructed using data from the GPS Earth Observation Network (GEONET), which consists of more than 1000 Global Positioning System (GPS) satellite receivers distributed over Japan. The data covered almost one solar activity period from April 1997 to June 2007. First, TECs were determined for 32 grid points, expanding from 27 to 45° N in latitude and from 127 to 145° E in longitude at 15-min intervals. Secondly, the time-latitude variation averaged over three days was determined by using the surface harmonic functional expansion. The coefficients of the expansion were then modeled by using a neural network technique with input parameters of the season (day of the year) and solar activity (F10.7 index and sunspot number). Thus, two-dimensional TEC maps (time vs. latitude) can be obtained for any given set of solar activity and day of the year.

scholarly journals MGR-DCB: A Precise Model for Multi-Constellation GNSS Receiver Differential Code Bias

2015 ◽  
Vol 69 (4) ◽  
pp. 698-708 ◽  
Author(s):  
Mohamed Abdelazeem ◽  
Rahmi N. Çelik ◽  
Ahmed El-Rabbany
Keyword(s):  
Total Electron Content ◽  
Satellite System ◽  
Mean Difference ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
International Gnss Service ◽  
Total Electron ◽  
Differential Code Bias ◽  
Gnss Receiver ◽  
Code Bias

In this study, we develop a Multi-constellation Global Navigation Satellite System (GNSS) Receiver Differential Code Bias (MGR-DCB) model. The model estimates the receiver DCBs for the Global Positioning System (GPS), BeiDou and Galileo signals from the ionosphere-corrected geometry-free linear combinations of the code observations. In order to account for the ionospheric delay, a Regional Ionospheric Model (RIM) over Europe is developed. GPS observations from 60 International GNSS Servoce (IGS) and EUREF reference stations are processed in the Bernese-5·2 Precise Point Positioning (PPP) module to estimate the Vertical Total Electron Content (VTEC). The RIM has spatial and temporal resolutions of 1° × 1° and 15 minutes, respectively. The receiver DCBs for three stations from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) are estimated for three different days. The estimated DCBs are compared with the MGEX published values. The results show agreement with the MGEX values with mean difference and Root Mean Square Error (RMSE) values less than 1 ns. In addition, the combined GPS, BeiDou and Galileo VTEC values are evaluated and compared with the IGS Global Ionospheric Maps (IGS-GIM) counterparts. The results show agreement with the GIM values with mean difference and RMSE values less than 1 Total Electron Content Unit (TECU).

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