NeQuick Model Research Articles

Ionospheric TEC and its irregularities over Egypt: a comprehensive study of spatial and temporal variations using GOCE satellite data

Abstract This study delves into ionospheric characteristics during solar cycle 24 using data from the Global Positioning System (GPS) and Low Earth Orbit (LEO) satellites, GOCE. The present study fills the gap of not assessing and studying GOCE satellite data before in Egypt. Focusing on spatial and temporal variations of ionospheric Total Electron Content (TEC) over Egypt and the Middle East across a 4-year dataset, monthly average Vertical Total Electron Content (VTEC) variations are scrutinized, emphasizing extremes during heightened and reduced solar and geomagnetic activities. Results TEC typically decreases with latitude’s increase, with peak ionization during equinoxes and troughs during solstices. Notably, VTEC values consistently reach maximum values on days of heightened solar and geomagnetic activities. GOCE data is evaluated against International Reference Ionosphere (IRI) model and NeQuick2 model by selecting 10 days from all data by using a statistical comparison via t-tests. There is not significant difference between them except for two days between GOCE-IRI. The values of Root Mean Square Error (RMSE) are 3.7403 and 4.4655 for GOCE – NeQuick2 model and GOCE – IRI model, respectively. Ionospheric scintillation, signifying rapid electron density fluctuations, is assessed through amplitude scintillation index (S4), S4 proxy, and Rate Of TEC Index (ROTI). A robust correlation between S4 and S4 proxy is noted, thus scintillation can be studied by using S4 proxy instead of S4. Temporal variations indicate heightened scintillation during geomagnetic storms and peak solar activity, contrasting with reduced activity during solar minimum. Throughout the study period the maximum scintillation index values for ROTI, S4, and S4 proxy are 0.3, 0.15, and 0.05, indicating minimal scintillation. This comprehensive analysis, rooted in GOCE data, illuminates spatial and temporal dynamics of ionospheric TEC and elucidates ionospheric scintillation characteristics in the Egypt region. These findings are crucial for refining ionospheric models, improving scintillation prediction, and enhancing satellite communication and navigation systems, especially in the study region.

Validation of the IRI-2020 model for the topside-plasmasphere using GNSS TEC measurements

The 2020 update of the International Reference Ionosphere (IRI) model introduces a new topside option, COR2, for the formulation of its electron density profile, as well as two plasmaspheric extension options based on the GCPM model of Gallagher et al. (2000) and the IMAGE/RPI model of Ozhogin et al. (2012). We validate the COR2-Gallagher and COR2-Ozhogin topside-plasmasphere options of IRI-2020 using GNSS VTEC measurements and compare them to the NeQuick model used as the default option in IRI-2016. VTEC data from a total of 21 GNSS ground-based receivers are compared to predictions of the IRI model, ranging from low (< 30°) to middle (30°-60°) magnetic latitudes, during high (year 2014; F10.7∼140 sfu) and low (year 2019; F10.7∼70 sfu) solar activity. Peak plasma frequency (foF2) data from co-located digisondes are ingested into the model to ensure the relevance of the comparison. The three topside-plasmasphere options perform equally well at mid-latitudes (RMSE∼3 TECU). At low latitudes, the NeQuick option (RMSE∼9 TECU) performs better than both the COR2-Gallagher and COR2-Ozhogin options (RMSE > 10 TECU). For all options, the modeled VTEC is consistently overestimated during the autumn/winter daytime at mid-latitudes regardless of solar activity, and throughout the day at low latitudes during low solar activity.

Effects of local time on the variations of the total electron contents at an American and Asian longitudes and their comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 models during solar cycle 24

Ionospheric modelling is one of the major tools to study the behavior of the ionosphere. Ionospheric models have been useful in predicting the true state of the ionosphere particularly in regions where Global Positioning System (GPS) are not readily available. This research paper aims to study the longitudinal variations and the effects of local time on the total electron content (TEC) recorded in two different sectors (Asia and America) during the ascending, maximum and descending phases of solar cycle 24 (2011–2017) and also to compare its values to IRI-2016, IRI-Plas2017 and NeQuick-2 models in order to evaluate their performances. An hourly interval profile computed on seasonal basis were used to study the behaviors of TEC diurnally and seasonally. A monthly interval error profile plotted on annual basis was also used to investigate the deviations of the models from the GPS values. Our results showed that the peak values of TEC in the Asian and American sectors were recorded around the dawn,06:00UT (13:00LT) and dusk, 18:00UT (15:00LT) respectively. We also affirmed from our results that seasonal/winter anomalies were recorded in all the phases of the solar cycle in both sectors. Equinoctial Asymmetry was also observed to be predominant during different phases of the solar cycle in both sectors except during ascending and descending phases in the Asian and American sectors respectively. Out of the 168 months of data collated for this study, only 162 months of data were available. The IRI-2016, IRI-Plas2017 and NeQuick-2 models have 11.7%, 23.5% and 64.8% better performance in all the months under consideration. Therefore, the NeQuick-2 model had the best performance in both the Asian and American sectors. Finally, from the results of our statistical analysis, Mean Absolute Error (MAE) has ∼3 TECU lower than the Root Mean Square Error (RMSE) values in both sectors and in all the solar cycle phase. Hence, MAE can evaluate the performance of ionospheric models better than RMSE.

An EOF-Based Global Plasmaspheric Electron Content Model and Its Potential Role in Vertical-Slant TEC Conversion

Topside total electron content (TEC) data measured by COSMIC/FORMAT-3 during 2008 and 2016 were used to analyze and model the global plasmaspheric electron content (PEC) above 800 km with the help of the empirical orthogonal function (EOF) analysis method, and the potential role of the proposed PEC model in helping Global Navigation Satellite System (GNSS) users derive accurate slant TEC (STEC) from existing high-precision vertical TEC (VTEC) products was validated. A uniform gridded PEC dataset was first obtained using the spherical harmonic regression method, and then, it was decomposed into EOF basis modes. The first four major EOF modes contributed more than 99% of the total variance. They captured the pronounced latitudinal gradient, longitudinal differences, hemispherical differences, diurnal and seasonal variations, and the solar activity dependency of global PEC. A second-layer EOF decomposition was conducted for the spatial pattern and amplitude coefficients of the first-layer EOF modes, and an empirical PEC model was constructed by fitting the second-layer basis functions related to latitude, longitude, local time, season, and solar flux. The PEC model was designed to be driven by whether solar proxy or parameters derived from the Klobuchar model meet the real-time requirements. The validation of the results demonstrated that the proposed PEC model could accurately simulate the major spatiotemporal patterns of global PEC, with a root-mean-square (RMS) error of 1.53 and 2.24 TECU, improvements of 40.70% and 51.74% compared with NeQuick2 model in 2009 and 2014, respectively. Finally, the proposed PEC model was applied to conduct a vertical-slant TEC conversion experiment with high-precision Global Ionospheric Maps (GIMs) and dual-frequency carrier phase observables of more than 400 globally distributed GNSS sites. The results of the differential STEC (dSTEC) analysis demonstrated the effectiveness of the proposed PEC model in aiding precise vertical-slant TEC conversion. It improved by 18.52% in dSTEC RMS on a global scale and performed better in 90.20% of the testing days compared with the commonly used single-layer mapping function.

On the variations in equatorial and low-latitude GPS-TEC and assessment of NeQuick-2, IRI-2016 and IRI-2020 models in the African longitude during solar cycle 24–25

Ionospheric models play a crucial role in understanding, prediction, and mitigation of the effects of ionospheric variability on a wide range of technological and scientific applications relying on space-based services. Conversely, the models need to be routinely updated with newer datasets and specifications to account for the regional discrepancies in the changing ionospheric conditions due to various dominant localized physical and chemical processes. Although there have been ongoing improvements to the extensively utilized empirical model known as the International Reference Ionosphere (IRI), the newly emerged version (IRI-2020) needs to undergo global testing. In this research, we carried out diurnal and seasonal variations in GPS-TEC and the assessment of some ionospheric models such as IRI-2016 and its recently updated version (IRI-2020), alongside the NeQuick-2 model at 2 stations each in the East, West and South in the equatorial and low-latitude African longitudes during different phases of solar cycles 24–25 (2016 – 2021). Also, we carried out statistical analysis between GPS-TEC and the ionospheric models using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), in order to show the model with the best forecasting capability in the African region. Diurnal, seasonal and solar cycle variations in GPS-TEC, NeQuick-2, IRI-2016 and IRI-2020 were observed, showing higher magnitudes in the West, followed by the East in close range and least in the Southern sector of the African longitudes. TEC Variations in some sectors in the African longitudes show a consistent trend in this research. More importantly, there are observed regional differences within the African longitudes owing to the wider coverage of landmass in the equatorial and low latitudes. However, TEC variations in the Northern sector of Africa are not included in the present research. From our observation, NeQuick-2 and IRI-2016 models either underestimate or overestimate GPS-TEC during different phases of the solar cycles at the three sectors in the African longitudes, whereas IRI-2020 shows mostly underestimating characteristics at the three sectors irrespective of solar activity conditions during the study period. Nevertheless, the underestimation or overestimation of NeQuick-2 and IRI-2016, and the underestimation of IRI-2020 are reflected in the RMSE and MAE values. Regrettably, the predictions from IRI-2020 model are not satisfactory at any of the three sectors in the African longitudes and prompt attention of the modeling community for further investigations towards possible refinements in the model specifications.

An Update of the NeQuick-Corr Topside Ionosphere Modeling Based on New Datasets

A new analytical formula for H0, one of the three parameters (H0, g, and r) on which the NeQuick model is based to describe the altitude profile of the electron density above the F2-layer peak height hmF2, has recently been proposed. This new analytical representation of H0, called H0,corr, relies on numerical grids based on two different types of datasets. On one side, electron density observations by the Swarm satellites over Europe from December 2013 to September 2018, and on the other side, IRI UP (International Reference Ionosphere UPdate) maps over Europe of the critical frequency of the ordinary mode of propagation associated with the F2 layer, foF2, and hmF2, at 15 min cadence for the same period. The new NeQuick topside representation based on H0,corr, hereafter referred to as NeQuick-corr, improved the original NeQuick topside representation. This work updates the numerical grids of H0,corr by extending the underlying Swarm and IRI UP datasets until December 2021, thus allowing coverage of low solar activity levels, as well. Moreover, concerning Swarm, besides the original dataset, the calibrated one is considered, and corresponding grids of H0,corr calculated. At the same time, the role of g is investigated, by considering values different from the reference one, equal to 0.125, currently adopted. To understand what are the best H0,corr grids to be considered for the NeQuick-corr topside representation, vertical total electron content data for low, middle, and high latitudes, recorded from five low-Earth-orbit satellite missions (COSMIC/FORMOSAT-3, GRACE, METOP, TerraSAR-X, and Swarm) have been analyzed. The updated H0,corr grids based on the original Swarm dataset with a value for g = 0.15, and the updated H0,corr grids based on the calibrated Swarm dataset with a value for g = 0.14, are those for which the best results are obtained. The results show that the performance of the different NeQuick-corr models is reliable also for low latitudes, even though these are outside the spatial domain for which the H0,corr grids were obtained, and are dependent on solar activity.

A novel ionospheric TEC mapping function with azimuth parameters and its application to the Chinese region

The ionospheric mapping function (MF) for Global Navigation Satellite System (GNSS), a mutual projection method for the slant total electron content (STEC) and vertical total electron content, is one of the significant factors affecting the performance of ionospheric models. The commonly used MF assumes isotropic TEC variations and takes into account only the satellite elevation angle, which may result in significant ionospheric projection errors, especially at low elevation angles. Based on the single-layer model, we propose an additional azimuth parameter mapping function (APMF). The APMF was estimated and evaluated by the NeQuick model during the periods of January 2014 and January 2022 from the aspect of simulation and measured STEC during the periods of 2014 and 2022 from the aspect of actual measurements over China, respectively. Compared to the modified single-layer model mapping function (MSLM-MF), the experimental results indicate that (1) The APMF can significantly reduce the ionospheric projection error, and the fluctuation in errors with different azimuth angles is small. (2) According to the evaluation based on the NeQuick simulation during the TEC peak time, when the ionosphere is quite active, the upper and lower quartiles of the absolute projection error boxplot of the APMF relative to the MSLM-MF in January 2014 are reduced by 56.1% and 60.0%, respectively, and in January 2022, they are reduced by 67.7% and 65.2%, respectively. Similarly, the upper whiskers in the boxplot are reduced by 54.7% and 67.5% in January 2014 and January 2022, respectively; the APMF performance in terms of the root mean square error (RMSE) is improved by 47.0% in January 2014 and 58.3% in January 2022. (3) According to the evaluation based on the measured STEC from GNSS raw data during the TEC peak time, the upper and lower quartiles of the absolute mapping error boxplot of the APMF relative to the MSLM-MF in 2014 are reduced by 48.9% and 46.9%, respectively, while in 2022, they are reduced by 48.3% and 41.2%, respectively. The upper whiskers in the boxplot are reduced by 41.8% and 35.2% in 2014 and 2022, respectively; the APMF performance in terms of RMSE is improved by 44.6% in 2014 and 39.2% in 2022.

Ionospheric equivalent slab thickness ingestion into the NeQuick model

The ionospheric equivalent slab thickness (τ), defined as the ratio of the vertical total electron content (vTEC) to the ionospheric F2-layer electron density maximum (NmF2), is a parameter providing useful information on the shape of the vertical electron density profile. However, the use of this information is of difficult practical application in empirical ionosphere models, such as the NeQuick model, because by design they do not explicitly include τ as a modelling parameter. In this work, we investigated the opportunity of using measured τ values to improve the empirical modelling of the ionosphere vertical electron density profile by NeQuick. Measured τ values were obtained through NmF2 observations and vTEC measurements obtained between 2001 and 2019 by an ionosonde and a ground-based GNSS receiver, respectively, co-located at Rome ionospheric station (41.8° N, 12.5° E; Italy). NeQuick τ was obtained as the ratio between modelled NmF2 and vTEC values, the latter obtained by integration of the vertical profile. As a first step, τ values modelled by NeQuick were compared with corresponding values measured at Rome station to highlight diurnal, seasonal, and solar activity differences. Then, measured τ values were ingested in NeQuick through a three-parameter assimilation procedure which first assimilate F2-layer peak characteristics to constrain the F2-layer anchor point, and then assimilate vTEC to optimize the F2-layer shape through the NeQuick F2-layer thickness parameter, namely B2bot. The assimilation procedure provides information on how the NeQuick B2bot has to be modified to match measured τ values, and then on how the shape of the F2-layer profile has to be changed accordingly. Our results highlight that, in many cases, the NeQuick B2bot has to be increased to match observations, which has implications on the modelling of the NeQuick bottomside and topside effective scale heights.

Performance analysis of NeQuick2 and IRI-Plas models during quiet geomagnetic and low solar activity conditions at Thanjavur equatorial location: Preliminary results

Performance analysis of NeQuick2 and IRI-Plas models during quiet geomagnetic and low solar activity conditions at Thanjavur equatorial location: Preliminary results

A Multi-Parameter Empirical Fusion Model for Ionospheric TEC in China’s Region

This article takes the measured Total Electron Content (TEC) from the GPS points of the China Regional Crust Observation Network as the starting point to establish a regional ionospheric empirical model. The model’s performance is enhanced by considering solar flux and geomagnetic activity data. The refinement function model of the ionospheric TEC diurnal variation component, seasonal variation component, and geomagnetic component is studied. Using the nonlinear least squares method to fit undetermined coefficients, MEFM-ITCR (Multi-parameter Empirical Fusion Model–Ionospheric TEC China Regional Model) is proposed to forecast the regional ionosphere TEC in China. The results show that the standard deviation of MEFM-ITCR residuals is 3.74TECU, and MEFM-ITCR fits the modeling dataset well. Analyses of geographic location variation, seasonal variation, and geomagnetic disturbance were carried out for MEFM-ITCR performance. The results indicate that in the Chinese region, MEFM-ITCR outperforms IRI2020 and NeQuick2 models in terms of forecast accuracy, linear correlation, and model precision for TEC measured using GPS points under different latitudes and longitudes, different seasons, and different geomagnetic disturbances. The empirical TEC model built for the Chinese region in this paper provides a new ionospheric delay correction method for GNSS single frequency users and is of great significance for establishing other new and improving existing ionospheric empirical models.

A simulation study of the Argo program-enhanced global ionospheric modeling

The ionospheric total electron content (TEC) is a critical parameter for space weather and Global Navigation Satellite System (GNSS) applications. Since 1998, the Ionospheric Working Group of the International GNSS Service (IGS) has been generating global ionospheric maps using data from hundreds of GNSS stations. However, the uneven geographical distribution of these observations has resulted in significant variations in TEC map accuracy, particularly in marine areas where observations are scarce or absent. In this study, we introduce Argo data as additional observations to enhance the accuracy of global ionospheric modeling. Argo data consists of measurements collected by more than 1,000 robotic floats deployed across the world's oceans. By utilizing the NeQuick model and considering the geographic coordinates of both IGS stations and Argo buoys, we simulate the ionospheric Slant Total Electron Content (STEC). This approach allows us to examine the impact of integrating Argo data into global ionospheric modeling and evaluate its effectiveness. The results indicate a significant improvement in the overall accuracy of the model after incorporating Argo data. Furthermore, by increasing the model's degree, a better global fit is achieved. It eliminates noticeable overestimation or underestimation of TEC, especially evident at a degree of 30. As the availability and uniform distribution of observations improve, the model demonstrates higher accuracy and enhanced global performance.

Analysis of GPS-TEC and IRI model over equatorial and EIA stations during solar cycle 24

Total Electron Content (TEC) measurements provided by Global Positioning System (GPS) as well as the International Reference Ionosphere – 2016 model (IRI01-Corr, IRI-2001, and NeQuick) model were compared at two Indian GPS stations: equatorial station Bangalore (12.580N, 77.350 E) and equatorial ionization anomaly (EIA) station Lucknow (26.500N, 80.550 E) during the solar cycle 24 extending from 2007 to 2017. The spectral, regression and statistical analysis displays a double-hump shape with counterclockwise hysteresis within TEC. The solar flux along with the TEC showed erratic as well as sluggish trends throughout the increasing period and flat and rapid throughout the decreasing period of the solar cycle 24. The semiannual and winter anomaly is discovered to be a constant feature throughout the solar cycle. The main idea of the current study is to investigate the performance of IRI01-Corr, IRI-2001, and NeQuick TEC in contrast to GPS TEC data throughout solar cycle 24 at the Indian equatorial and EIA stations. The modeled TEC data exhibit almost complete agreement with the measurement highlighting the same trends in the solar cycle as well as semiannual and seasonal changes. However, there are clear biases between the observed and modeled TECs when local time, seasons, as well as solar activity phases are considered. The main findings of this paper are that the NeQuick model generally underestimates noon-time TEC while the IRI-2001 model overestimates the same. The error in estimating noontime TEC from the IRI model using IRI-2001 as a topside at the EIA station is higher (142 %) than that at the equatorial station (42 %).

Parametric Dependence of Topside Ionospheric Empirical Scale Height and Electron Density Profiles in NeQuick2 Model Over the Equatorial and Low Latitudes and Its Consequences on the Estimation of TEC

AbstractConstructing realistic vertical electron density profiles is a crucial step in accurately estimating the ionospheric total electron content (TEC) in empirical models. Inadequate representation of electron density profiles leads to under‐ or over‐estimation of TEC in model outputs. One of the widely used ionospheric empirical model, the NeQuick2 exhibits large uncertainties over equatorial and low latitudes, particularly in the topside ionosphere. The NeQuick2 model employs semi Epstein type of polynomials to characterize the topside ionospheric structure, wherein, the scale height (H) is the key parameter. NeQuick2 model estimates H value using empirical formulations, which contain three major parameters namely, Ho—the scale height at the F‐layer peak, g—height gradient in H, and r—which controls the increase in H at higher altitudes. In this study, a systematic analysis has been carried out with particular focus on the equatorial and low latitudes to explore the variability of topside scale height and electron density profiles on the above three empirical parameters using COSMIC observations over Trivandrum and Ahmedabad, in India. Model uncertainties in estimating Ho and their impacts on the estimation of TEC are investigated. Data assimilation analysis has been carried out to obtain a quantitative understanding on the effect of deviations in topside scale height on the uncertainties in accurate estimation of TEC over equatorial and low latitudes. This study reveals the impact of scale height uncertainties on errors in modeled TEC and demonstrates the need for improvement in empirical formulations for improving accuracies in ionospheric modeling over equatorial and low latitude sectors.

Performance of a locally adapted NeQuick-2 model during high solar activity over the Brazilian equatorial and low-latitude region

The Brazilian equatorial and low-latitude regions are subject to various dynamic and electrodynamics processes. As a result, ionospheric modeling over this region remains a challenge. In this article, we present the results of first observation of data ingestion into the climatological model, NeQuick during both quiet and disturbed conditions over Brazil. The variation of the daily F10.7 solar radio flux, the main driver of the NeQuick model, strongly influences its performance in both space and time, especially during high solar activity. With data ingestion, using the local level of ionization, NeQuick’s performance can be improved. We developed an algorithm to obtain the local effective ionization parameters (Az1 and Az2) using a single station, in the equatorial trough and low-latitude regions, which are subsequently used in the NeQuick to reproduce vTEC at co-located stations. The model’s input (effective ionization level) was obtained when the modeled vTEC best fits the measured vTEC at the reference stations Maraba (5.35° S, 49.11° S, dip lat.: 3.06° S; MABA) and Ourinhos (22.93° S, 49.88° S, dip lat.: 17.42° S; OURI). Statistical results show that the model’s performance greatly improves after data ingestion, reproducing vTEC at all latitudes close to the reference stations in 2014. We found that NeQuick improved by 71 %, 74 %, 83 %, and 69 % after ingestion during the storm periods of 17–21 February, 10–14 April, 6–10 June, and 23–27, December in the low-latitude region at SJSP. Using the Az1 values obtained at MABA and Az3 at SALU during July 2014, NeQuick reproduces the critical frequency of the F2 layer with a percentage improvement of approximately 20 % and 37 % respectively.

Comparative Assessment of the Performances of GPS‐TEC Assisted NTCM, NeQuick2 and Neural Network Models to Describe the East‐African Equatorial Ionosphere

AbstractDifferent ionospheric climatological models such as NeQuick2 and NTCM have been developed to mitigate the ionosphere impact on the trans‐ionosphere propagating radio wave. Moreover, the Neural Network (NN) is used to model and characterize the ionosphere. However, no one has compared the performances of NeQuick2, NTCM, and NN after adapting to GPS TEC. This study evaluates their performances in the East‐African region in 2013 and 2015. It has been done by computing their drivers (effective ionization level, Az for NeQuick2 and ionization driving index, Id for NTCM) through least‐square fitting to TEC observation sense. NN‐algorithm has also been trained and tested with observed TEC used for NeQuick2 and NTCM adaptation. The annual performance test has shown that the correlation coefficient (R) values between observed and NTCM modeled TEC, after an adaption, are better than the corresponding values obtained from NeQuick2 and NN. It also shows that the standard deviations (STD) and root‐mean‐square errors (RMSE) obtained for NTCM are smaller than the STD and RMSE computed for NeQuick2 and NN. On the other hand, the daily performance test of now‐casting and predicting showed that the NN performs the best, followed by NTCM. However, the 1‐hr prediction test showed that NTCM performs the best among the models considered in this study.

Modeling the Topside Ionosphere Effective Scale Height through In Situ Electron Density Observations by Low-Earth-Orbit Satellites

In this work, we aim to characterize the effective scale height at the ionosphere F2-layer peak (H0) by using in situ electron density (Ne) observations by Langmuir Probes (LPs) onboard the China Seismo-Electromagnetic Satellite (CSES—01). CSES—01 is a sun-synchronous satellite orbiting at an altitude of ~500 km, with descending and ascending nodes at ~14:00 local time (LT) and ~02:00 LT, respectively. Calibrated CSES—01 LPs Ne observations for the years 2019–2021 provide information in the topside ionosphere, whereas the International Reference Ionosphere model (IRI) provides Ne values at the F2-layer peak altitude for the same time and geographical coordinates as CSES—01. CSES—01 and IRI Ne datasets are used as anchor points to infer H0 by assuming a linear scale height in the topside representation given by the NeQuick model. COSMIC/FORMOSAT—3 (COSMIC—1) radio occultation (RO) data are used to constrain the vertical gradient of the effective scale height in the topside ionosphere in the linear approximation. With the CSES—01 dataset, we studied the global behavior of H0 for daytime (~14:00 LT) and nighttime (~02:00 LT) conditions, different seasons, and low solar activity. Results from CSES—01 observations are compared with those obtained through Swarm B satellite Ne-calibrated measurements and validated against those from COSMIC—1 RO for similar diurnal, seasonal, and solar activity conditions. H0 values modeled by using CSES—01 and Swarm B-calibrated observations during daytime both agree with corresponding values obtained directly from COSMIC—1 RO profiles. Differently, H0 modeling for nighttime conditions deserves further investigation because values obtained from both CSES—01 and Swarm B-calibrated observations show remarkable and spatially localized differences compared to those obtained through COSMIC—1. Most of the H0 mismodeling for nighttime conditions can probably to be attributed to a sub-optimal spatial representation of the F2-layer peak density made by the underlying IRI model. For comparison, H0 values obtained with non-calibrated CSES—01 and Swarm B Ne observations are also calculated and discussed. The methodology developed in this study for the topside effective scale height modeling turns out to be applicable not only to CSES—01 satellite data but to any in situ Ne observation by low-Earth-orbit satellites orbiting in the topside ionosphere.

Improving topside ionospheric empirical model using FORMOSAT-7/COSMIC-2 data

The precise description of the topside ionosphere using an ionospheric empirical model has always been a work in progress. The NeQuick topside model is greatly enhanced by adopting radio occultation data from the FORMOSAT-7/COSMIC-2 constellation. The topside scale height H formulation in the NeQuick model is simplified into a linear combination of an empirically deduced parameter H0 and a gradient parameter g. The two-dimensional grid maps for the H0 and g parameters are generated as a function of the foF2 and hmF2 parameters. Corrected H0 and g values can be interpolated easily from two grid maps, allowing a more accurate description of the topside ionosphere than the original NeQuick model. The improved NeQuick model (namely NeQuick_GRID model) is statistically validated by comparing it to Total Electron Content (TEC) integrated from COSMIC-2 electron density profiles and space-borne TEC derived from onboard Global Navigation Satellite System observations, respectively. The results show that the NeQuick_GRID model can reduce relative errors by 38% approximately when compared to the integrated TEC from COSMIC profiles and by 15% approximately when compared to the space-borne TEC. Furthermore, a long-term statistical analysis during years of both high and low solar activities reveals that grid maps of the scale factor H0 and the gradient parameter g have very similar features, allowing rapid and efficient acquisition of high-precision electron density during different solar activity.

Analysis of GPS/EGNOS Positioning Quality Using Different Ionospheric Models in UAV Navigation.

Unmanned aerial vehicles (UAVs) have become very popular tools for geoinformation acquisition in recent years. They have also been applied in many other areas of life. Their navigation is highly dependent on global navigation satellite systems (GNSS). The European Geostationary Navigation Overlay Service (EGNOS) is intended to support GNSSs during positioning, mainly for aeronautical applications. The research presented in this paper concerns the analysis of the positioning quality of a modified GPS/EGNOS algorithm. The calculations focus on the source of ionospheric delay data as well as on the aspect of smoothing code observations with phase measurements. The modifications to the algorithm concerned the application of different ionospheric models for position calculation. Consideration was given to the EGNOS ionospheric model, the Klobuchar model applied to the GPS system, the Klobuchar model applied to the BeiDou system, and the NeQuick model applied to the Galileo system. The effect of removing ionospherical corrections from GPS/EGNOS positioning on the results of the determination of positioning quality was also analysed. The results showed that the original EGNOS ionospheric model maintains the best accuracy results and a better correlation between horizontal and vertical results than the other models examined. The additional use of phase-smoothing of code observations resulted in maximum horizontal errors of approximately 1.3 m and vertical errors of approximately 2.2 m. It should be noted that the results obtained have local characteristics related to the area of north-eastern Poland.

Ionospheric Tomography: A Compressed Sensing Technique Based on Dictionary Learning

GNSS (Global Navigation Satellite System) observation insufficiency limits the development of the voxel-based computerized ionospheric tomography (CIT) technique. Electron densities of voxels without observation cannot be accurately estimated by the commonly used algebraic reconstruction techniques. In this study, we proposed a compressed sensing technique (CST) based on dictionary learning for ionospheric tomography. Specifically, the K-SVD (singular value decomposition) algorithm was used for dictionary learning based on training sets that are derived from the NeQuick model, hereafter referred to as the CST_NeQuick algorithm. K-SVD uses the orthogonal matching pursuit (OMP) for sparse coding and the SVD approach for dictionary updating. Both simulations and real experiments demonstrated the feasibility and superiority of the CST algorithm when compared to the widely used multiplicative algebraic reconstruction technique (MART). It was found that the CST_NeQuick algorithm’s tomographic performances were mostly superior to those of the MART algorithm in comparison with the independent slant total electron content (STEC) references. Another CST-based tomographic experiment was performed by using the MART-based solutions for dictionary learning, hereafter referred to as the CST_MART algorithm. It showed that the CST_MART algorithm can reduce the average root mean square (RMS) of the CIT-derived STEC by 37.3 % and 20.2 %, respectively, when compared to the MART and CST_NeQuick algorithms. Besides, the CST_MART algorithm’s electron density profiles also showed more agreement with the electron density profiles that were derived from radio occultation data.

Ionospheric climate index as a driving parameter for the NeQuick model

Ionospheric delay is one of the significant error sources for global navigation satellite system (GNSS) positioning. GNSSs broadcast the coefficients of the ionospheric model to correct ionospheric delay for single-frequency users. A modified three-dimensional model (NeQuick G) based on the NeQuick climatological model is adopted for Galileo users. The NeQuick G model uses the effective ionization level (Az) instead of the sunspot number as the driving parameter. In this study, we introduce the ionospheric climate index (ICI) as a new driving parameter for the NeQuick model. In comparison, the ICI-driven NeQuick model has a better performance than the Az-driven NeQuick G model at both low and high latitudes. In addition, only one GNSS station at low latitudes is required to calculate the ICI, which would save maintenance costs and improve the efficiency of updating the broadcast coefficients. This model has potential application value for future upgrades of Galileo’s ionospheric broadcast model.