scholarly journals Validation and application of optimal ionospheric shell height model for single-site estimation of total electron content

2019 ◽  
Vol 37 (2) ◽  
pp. 263-271
Author(s):  
Jiaqi Zhao ◽  
Chen Zhou

Abstract. We recently proposed a method to establish an optimal ionospheric shell height model based on the international GNSS service (IGS) station data and the differential code bias (DCB) provided by the Center for Orbit Determination in Europe (CODE) during the time from 2003 to 2013. This method is very promising for DCB and accurate total electron content (TEC) estimation by comparing to the traditional fixed shell height method. However, this method is basically feasible only for IGS stations. In this study, we investigate how to apply the optimal ionospheric shell height derived from IGS station to non-IGS stations or isolated GNSS receivers. The intuitive and practical method to estimate TEC of non-IGS stations is based on optimal ionospheric shell height derived from nearby IGS stations. To validate this method, we selected two dense networks of IGS stations located in regions in the US and Europe. Two optimal ionospheric shell height models are established by two reference stations, namely GOLD and PTBB, which are located at the approximate center of two selected regions. The predicted daily optimal ionospheric shell heights by the two models are applied to other IGS stations around these two reference stations. Daily DCBs are calculated according to these two optimal shell heights and compared to respective DCBs released by CODE. The validation results of this method are as follows. (1) Optimal ionospheric shell height calculated by IGS stations can be applied to its nearby non-IGS stations or isolated GNSS receivers for accurate TEC estimation. (2) As the distance away from the reference IGS station becomes larger, the DCB estimation error becomes larger. The relation between the DCB estimation error and the distance is generally linear.

2018 ◽  
Author(s):  
Jiaqi Zhao ◽  
Chen Zhou

Abstract. We recently proposed a method to establish optimal ionospheric shell height model based on the international GNSS service (IGS) station data and the differential code bias (DCB) provided by Center for Orbit Determination in Europe (CODE) during the time from 2003 to 2013. This method is very promising for DCB and accurate total electron content (TEC) estimation by comparing to traditional fixed shell height method. However, this method is basically feasible only for IGS stations. In this study, we investigate how to apply the optimal ionospheric shell height derived from IGS station to non-IGS stations or isolated GNSS receivers. The intuitional and practical method to estimate TEC of non-IGS stations is based on optimal ionospheric shell height derived from nearby IGS stations. To validate this method, we selected two dense networks of IGS stations located in US and Europe region. Two optimal ionospheric shell height models are established by two reference stations, namely GOLD and PTBB, which are located at the approximate center of two selected regions. The predicted daily optimal ionospheric shell heights by the two models are applied to other IGS stations around these two reference stations. Daily DCBs are calculated according to these two optimal shell heights and compared to respective DCBs released by CODE. The validation results of this method present that 1) Optimal ionospheric shell height calculated by IGS stations can be applied to its nearby non-IGS stations or isolated GNSS receivers for accurate TEC estimation. 2) As the distance away from the reference IGS station becomes larger, the DCB estimation error becomes larger. The relation between the DCB estimation error and the distance is generally linear.


2020 ◽  
Vol 10 ◽  
pp. 11 ◽  
Author(s):  
Claudio Cesaroni ◽  
Luca Spogli ◽  
Angela Aragon-Angel ◽  
Michele Fiocca ◽  
Varuliator Dear ◽  
...  

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.


2019 ◽  
Vol 11 (6) ◽  
pp. 706 ◽  
Author(s):  
Jiandi Feng ◽  
Baomin Han ◽  
Zhenzhen Zhao ◽  
Zhengtao Wang

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.


2013 ◽  
Vol 19 (2) ◽  
pp. 227-246 ◽  
Author(s):  
Wagner Carrupt Machado ◽  
Edvaldo Simões da Fonseca Junior

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.


2019 ◽  
Vol 11 (17) ◽  
pp. 2062
Author(s):  
Di Wang ◽  
Xiaowen Luo ◽  
Jinling Wang ◽  
Jinyao Gao ◽  
Tao Zhang ◽  
...  

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.


2021 ◽  
pp. 14-21
Author(s):  
P. А. Budnikov ◽  
◽  
V. V. Alpatov ◽  

The features of using survey GNSS receivers for real-time ionosphere monitoring based on high orbital ionosphere tomography network are presented. The related problems and solutions methods are described. The algorithms for calculating total electron content and scintillation indices, that allow reducing errors and noise, are proposed. Special attention is given to the methods reducing data loss during processing. A model of the electron content peak height used for mapping ionospheric parameters is also introduced.


2020 ◽  
Author(s):  
Takashi Maruyama ◽  
Kornyanat Hozumi ◽  
Guanyi Ma ◽  
Pornchai Supnithi ◽  
Qingtao Wan

Abstract A new technique was developed to estimate the ionospheric total electron content (TEC) from Global Navigation Satellite System (GNSS) satellite signals. The vertically distributed electron density was parameterized by two thin-shell layers (double-shell approach). The spatiotemporal variation of TEC (strictly speaking, partial electron content) associated with each shell was approximated by the functional fitting of spherical surface harmonics. The major improvements over the conventional single-shell approach were as follows: (1) the precise estimation of TEC was achieved; (2) the estimated TEC was less dependent on the choice of shell height; and (3) the equatorial anomaly was captured more correctly. Furthermore, higher and lower shells exhibited a different pattern of local time vs latitude variation, providing information on the ionosphere--thermosphere dynamics.


2015 ◽  
Vol 69 (4) ◽  
pp. 698-708 ◽  
Author(s):  
Mohamed Abdelazeem ◽  
Rahmi N. Çelik ◽  
Ahmed El-Rabbany

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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