Disturbed Ionospheric Conditions Research Articles

LOFAR PL610 Station Data Product Specification

ABSTRACT Since 2017, the Space Research Centre of the Polish Academy of Sciences in Warsaw, Poland, has measured and gathered over 35,000 hours of observations with the use of the LOw Frequency ARray (LOFAR) radio telescope. This paper outlines the Standard Data Product acquired from the LOFAR PL610 station located in Borówiec, Poland. Within this context, we detail the data products that are accessible, provide metadata descriptions for them, and include an example of the data under both quiet and disturbed ionospheric conditions.

Simultaneous monitoring of the limited area ionosphere with the use of GPS and ionosonde

The importance of this study lies in its contribution to the field of ionospheric science, particularly in the monitoring and prediction of ionospheric parameters. This study focuses on comparing two techniques for spatio-temporal kriging of critical ionospheric parameters, namely the F2 layer critical frequency (foF2) and Total Electron Content (TEC), under both quiet and disturbed ionospheric conditions. The first technique, Ordinary Kriging (OK), relies solely on foF2 data, while the second technique, Kriging with External Drift (KED), incorporates the dynamic relationship between foF2 and TEC data to improve the interpolation process. This study demonstrates how KED, which utilizes dynamic secondary information, offers advantages over OK. By simultaneously monitoring the ionosphere from a single ionosonde station and collecting data from visible GPS satellites, KED enhances the accuracy of spatial structural analysis, enabling more precise estimations of ionospheric characteristics across interpolation grid nodes. The research highlights that the non-uniform distribution of ionosonde stations, especially in regions with limited foF2 data, can benefit from KED's incorporation of TEC data. Additionally, the study reveals the potential for improving TEC maps by assimilating foF2 data located at the periphery of the observation area. Furthermore, the paper discusses the determination of semivariogram structures for both foF2 and TEC data, emphasizing the spatial correlations between data points. These findings contribute to a better understanding of ionospheric behavior and the potential for enhanced ionospheric modeling.

Geomagnetic storm effect on equatorial ionosphere over Sri Lanka through total electron content observations from continuously operating reference stations network during Mar–Apr 2022

Abstract The technological advancements in the current era have highlighted the increasing significance of satellite-based positioning, navigation, and timing services in a wide range of dynamic and critical applications. This has led to significant efforts towards enhancing the performance of global navigation satellite systems (GNSS) operating under challenging ionospheric conditions. The Sri Lankan ionosphere region is a focal point of equatorial aeronomy scientists, being situated in the southernmost landmass of the Indian longitude sector within the vicinity of the magnetic equator where a combination of electric, wind, and temperature dynamics exerts a substantial influence on the ionosphere but was relatively unexplored in the past. In the present work, we employed a Kriging interpolation technique on the total electron content (TEC) variables from ten GNSS receivers operating under the Continuously Operating Reference Stations (CORS) network in Sri Lanka first ever of its kind to deliver two-dimensional regional ionospheric TEC maps at hourly intervals, both during quiet and disturbed ionospheric conditions in the equinoctial March and April months of 2022. The latitudinal variation patterns are discernable from the hourly TEC maps. Furthermore, a comparative analysis of the performance of GNSS-derived TEC with that of the routinely published Global Ionospheric Maps (GIMs) confirms overestimation characteristics of the latter irrespective of the local time of observation. The generated regional ionospheric maps are fairly responsive to the onset of the storm and the recovery phase thereafter. The extent of nighttime ionospheric irregularity is also probed through the rate of TEC index (ROTI) variations, demonstrating that the irregularities were insignificant during the selected storm event.

Identifying spurious cycle slips based on iterative filtering under disturbed ionospheric conditions for undifferenced GNSS observations

The TurboEdit method is widely used to detect cycle slips on the global navigation satellite system (GNSS) carrier-phase measurements. However, it leads to an increasing number of false alarms in detecting cycle slips under disturbed ionospheric conditions. Besides, once the method detects a cycle slip at one satellite, it treats dual frequencies with cycle slips rather than at one frequency. Considering these two challenges, we developed a solution-based iterative filter detection method to reduce the number of spurious cycle slip detection under disturbed ionospheric conditions. The method initially assumes that there is no cycle slip at each frequency. We then estimate the solutions without cycle slips. A decision of exiting cycle slips is made by examining and comparing the two results solutions with or without cycle slips in terms of usable satellites, ambiguities, and residuals. The uncombined precise point positioning (PPP) during disturbed ionospheric conditions on 17 March 2015 at high latitude was studied to validate the proposed method. Results showed that the detected number of spurious cycle slips was reduced significantly. With fewer marked cycle slips, more stable and smoother positioning performance was achieved when fewer ambiguity parameters were reinitialized.

Investigating GNSS PPP\u2013RTK with external ionospheric constraints

Real-Time Kinematic Precise Point Positioning (PPP–RTK) is inextricably linked to external ionospheric information. The PPP–RTK performances vary much with the accuracy of ionospheric information, which is derived from different network scales, given different prior variances, and obtained under different disturbed ionospheric conditions. This study investigates the relationships between the PPP–RTK performances, in terms of precision and convergence time, and the accuracy of external ionospheric information. The statistical results show that The Time to First Fix (TTFF) for the PPP–RTK constrained by Global Ionosphere Map (PPP–RTK-GIM) is about 8–10 min, improved by 20%–50% as compared with that for PPP Ambiguity Resolution (PPP-AR) whose TTFF is about 13–16 min. Additionally, the TTFF of PPP–RTK is 4.4 min, 5.2 min, and 6.8 min, respectively, when constrained by the external ionospheric information derived from different network scales, e.g. small-, medium-, and large-scale networks, respectively. To analyze the influences of the optimal prior variances of external ionospheric delay on the PPP–RTK results, the errors of 0.5 Total Electron Content Unit (TECU), 1 TECU, 3 TECU, and 5 TECU are added to the initial ionospheric delays, respectively. The corresponding convergence time of PPP–RTK is less than 1 min, about 3, 5, and 6 min, respectively. After adding the errors, the ionospheric information with a small variance leads to a long convergence time and that with a larger variance leads to the same convergence time as that of PPP-AR. Only when an optimal prior variance is determined for the ionospheric delay in PPP–RTK model, the convergence time for PPP–RTK can be shorten greatly. The impact of Travelling Ionospheric Disturbance (TID) on the PPP–RTK performances is further studied with simulation. It is found that the TIDs increase the errors of ionospheric corrections, thus affecting the convergence time, positioning accuracy, and reliability of PPP–RTK.

Ordered Subsets-Constrained ART Algorithm for Ionospheric Tomography by Combining VTEC Data

Computerized ionospheric tomography is an important technique for ionosphere investigation. However, it is an ill-posed problem owing to an insufficient amount of available data, because of which the distributions of ionospheric electron density (IED) cannot be reconstructed accurately. In light of this, the ordered subsets-constrained algebraic reconstruction technique (OS_CART) is developed here using vertical total electron content (VTEC) data to solve this problem, where the VTEC derived from the slant total electron content (STEC) of Global Navigation Satellite System (GNSS) signal paths is used to compensate for the lack of data provided by GNSS observations in inversion regions, and the OS_CART is also used to improve the spatial resolution and inversion efficiency. The proposed method was validated by conducting numerical experiments using GNSS and independent ionosonde data in both quiescent and disturbed ionospheric conditions. In contrast to classical methods of ionospheric tomography, the proposed method exhibited significantly higher reconstruction accuracy. While delivering a comparable accuracy to that of traditional methods in terms of self-consistency validation using STEC data and without overfitting, the proposed method yielded a more than 90% improvement over the self-consistency validation using VTEC data. In addition, a better daily description of the ionosphere was obtained using the proposed method, where an increase in the peak height and irregular changes to the IED, associated with variations in the number of epochs and the occurrence of magnetic storms, were observed. Overall, the results reveal that the proposed method is a useful tool for research on space weather.

A new three-dimensional computerized ionospheric tomography model based on a neural network

Computerized ionospheric tomography (CIT) is an ill-posed inverse problem owing to insufficient data acquisition. Therefore, the ionospheric electron density (IED) distributions cannot be reconstructed accurately. Although many attempts have been made to deal with this issue, there is still a long way to go before it can be completely overcome. Specifically, the inverted IEDs of voxels without observational information show a strong dependence on initial values, which affects the overall accuracy of CIT. Taking this into account, a new three-dimensional CIT model is developed, based on a backpropagation neural network. The neural network model is trained using the characteristics and inverted IEDs of voxels with observational information, and then, the IEDs of voxels without observational information are predicted again. Careful validation of the proposed model is performed by conducting numerical experiments with GPS simulation and real data under both quiet and disturbed ionospheric conditions. Compared with the traditional non-neural network method in the simulation experiment, the proposed method offers improvements of 62.0 and 56.89% in root mean square error and the mean absolute error for those voxels without observational information, respectively, while it offers improvements of 30.98 and 26.67% for all voxels of the whole region. In the real data experiment, the IEDs of the control groups obtained by the proposed method are compared with the target IEDs for all periods. The result presents correlation coefficient greater than 0.96 between this predicted IEDs and the target IEDs for all periods, and this further certifies the feasibility of the proposed method. Additionally, the latitude–longitude maps and profiles of the ionospheric electron density also show that the ill-posedness problem has a significantly weaker effect for those voxels without observational information.

Ionospheric time delay corrections based on the extended single layer model over low latitude region

Ionospheric delay error is considered to be one of the most prominent factors impacting the Global Navigation Satellite Systems (GNSS) positioning and navigation accuracies. Due to dispersive nature and anisotropic of the ionosphere above certain regions, the positioning accuracy is seriously affected when using a precision-limited model. In this paper, an attempt has been taken to estimate ionosphere-delays based on Planar Fit (PF) and Spherical Harmonic Function (SHF) models by applying the commonly used single layer Model (SLM) and an extended single layer model (ESLM) which has been explored sparsely over the region. The results show that ESLM of PF and SHF techniques performed better in estimating ionospheric delay compared to the existing SLM model. Although the performance of the ESLM approach is almost comparable to the SLM results during the quiet ionospheric conditions, the ESLM-PF and ESLM-SHF models led to respective improvements of 4.66% and 7.14% over the classically used SLM model under the disturbed ionospheric conditions. In view of the uneven variability of equatorial/low latitude ionosphere above the Indian subcontinental region, the suitability of ESLM-PF and ESLM-SHF models has been emphasized and suggested for assessing its completeness and reliableness across other parts of the globe. The output of this work may be useful for high precession GNSS positioning through mitigating the ionospheric delays under quiet as well as varied ionospheric conditions across the low/equatorial latitude regions.

Estimation of ionospheric gradients and vertical total electron content using dual-frequency NAVIC measurements

Indian Space Research Organization is being developing a regional satellite radio navigation system known as Navigation with Indian Constellation (NAVIC) satellite system to cater positioning, navigation and timing application. NAVIC has the capability to transmit dual frequency measurements on L5 and S band signals. Ionospheric gradients are one of the pre-dominant error sources with huge impact at the time of geomagnetic disturbed ionospheric conditions in low-latitude region. The large ionospheric gradients can degrade the positional accuracy of NAVIC system. In this paper, ionospheric temporal gradient analysis is carried out in east, west, north and south directions using a Weighted Least Squares (WLS) algorithm for NAVIC L5 signals. The ionospheric gradient algorithm is tested with NAVIC receiver data located at Koneru Lakshmaiah Education Foundation (KLEF) University campus, Guntur, India (16.42∘ N, 80.62∘ E) during geomagnetic storm time conditions (27th–29th May 2017). The results confirmed the increments in VTEC along with longitudinal (E-W) and latitudinal (N-S) gradient magnitudes accordingly with geomagnetic storm effects. The WLS based VTEC model is able to detect E and W ionospheric gradients during the transition period from main phase to recovery phase of the geo-magnetic storm.

On the estimation of higher-order ionospheric effects in precise point positioning

Higher-order ionospheric effects, if not properly accounted for, can propagate into geodetic parameter estimates. For this reason, several investigations have led to the development and refinement of formulas for the correction of second- and third-order ionospheric errors, bending effects and total electron content variations due to excess path length. Standard procedures for computing higher-order terms typically rely on slant total electron content computed either from global ionospheric maps (GIMs) or using GNSS observations corrected using differential code biases (DCBs) provided by an external process. In this study, we investigate the feasibility of estimating slant ionospheric delay parameters accounting for both first- and second-order ionospheric effects directly within a precise point positioning (PPP) solution. It is demonstrated that proper handling of the receiver DCB is critical for the PPP method to provide unbiased estimates of the position. The proposed approach is therefore not entirely free from external inputs since GIMs are required for isolating the receiver DCB, unless the latter is provided to the PPP filter. In terms of positioning performance, the PPP approach is capable of mitigating higher-order ionospheric effects to the same level as existing approaches. Due to the inherent risks associated with constraining slant ionospheric delay parameters in PPP during disturbed ionospheric conditions, the reliability of the method can be greatly enhanced when the receiver DCB is available a priori, such as for permanent GNSS stations.

Mitigation of Ionospheric Effect on Multi-GNSS Positioning with Ionosphere Delay Estimation Using Single-Frequency Measurements of Selected Satellites

Ionosphere delay is the largest source of positioning error for single point positioning using single-frequency receiver of global navigation satellite system (GNSS). To mitigate the effect of ionosphere which varies sometimes rapidly and locally due to the solar activity, we propose estimating the ionosphere delay in the process of positioning calculation by using the ionospheric thin shell model with single-frequency pseudorange measurement of single epoch. Since sufficient number of visible satellites is observable for multi-GNSS positioning, all those measurements are not necessarily used. We propose algorithm of selecting useful satellites by the residual ranging error of pseudorange measurement to mitigate the positioning error. The performance evaluation for proposed selection algorithm and ionosphere delay estimation was conducted by using L1 pseudorange measurements of global positioning system (GPS) and GLONASS on both quiet and disturbed ionospheric conditions. Proposed selection algorithm reduced the rms of horizontal positioning error by about 10% on disturbed condition. Proposed ionosphere delay estimation increased the average of horizontal error reduction by 30% in daytime on disturbed condition, compared with the conventional correction method using Klobuchar model.

Performance of ionospheric maps in support of long baseline GNSS kinematic positioning at low latitudes

AbstractIonospheric scintillation occurs mainly at high and low latitude regions of the Earth and may impose serious degradation on GNSS (Global Navigation Satellite System) functionality. The Brazilian territory sits on one of the most affected areas of the globe, where the ionosphere behaves very unpredictably, with strong scintillation frequently occurring in the local postsunset hours. The correlation between scintillation occurrence and sharp variations in the ionospheric total electron content (TEC) in Brazil is demonstrated in Spogli et al. (2013). The compounded effect of these associated ionospheric disturbances on long baseline GNSS kinematic positioning is studied in this paper, in particular when ionospheric maps are used to aid the positioning solution. The experiments have been conducted using data from GNSS reference stations in Brazil. The use of a regional TEC map generated under the CALIBRA (Countering GNSS high‐Accuracy applications Limitations due to Ionospheric disturbances in BRAzil) project, referred to as CALIBRA TEC map (CTM), was compared to the use of the Global Ionosphere Map (GIM), provided by the International GNSS Service (IGS). Results show that the use of the CTM greatly improves the kinematic positioning solution as compared with that using the GIM, especially under disturbed ionospheric conditions. Additionally, different hypotheses were tested regarding the precision of the TEC values obtained from ionospheric maps, and its effect on the long baseline kinematic solution evaluated. Finally, this study compares two interpolation methods for ionospheric maps, namely, the Inverse Distance Weight and the Natural Neighbor.

Simultaneous multiplicative column-normalized method (SMART) for 3-D ionosphere tomography in comparison to other algebraic methods

Abstract. The accuracy and availability of satellite-based applications like GNSS positioning and remote sensing crucially depends on the knowledge of the ionospheric electron density distribution. The tomography of the ionosphere is one of the major tools to provide link specific ionospheric corrections as well as to study and monitor physical processes in the ionosphere. In this paper, we introduce a simultaneous multiplicative column-normalized method (SMART) for electron density reconstruction. Further, SMART+ is developed by combining SMART with a successive correction method. In this way, a balancing between the measurements of intersected and not intersected voxels is realised. The methods are compared with the well-known algebraic reconstruction techniques ART and SART. All the four methods are applied to reconstruct the 3-D electron density distribution by ingestion of ground-based GNSS TEC data into the NeQuick model. The comparative case study is implemented over Europe during two periods of the year 2011 covering quiet to disturbed ionospheric conditions. In particular, the performance of the methods is compared in terms of the convergence behaviour and the capability to reproduce sTEC and electron density profiles. For this purpose, independent sTEC data of four IGS stations and electron density profiles of four ionosonde stations are taken as reference. The results indicate that SMART significantly reduces the number of iterations necessary to achieve a predefined accuracy level. Further, SMART+ decreases the median of the absolute sTEC error up to 15, 22, 46 and 67 % compared to SMART, SART, ART and NeQuick respectively.

Comparing different assimilation techniques for the ionospheric F2 layer reconstruction

AbstractFrom the applications perspective the electron density is the major determining parameter of the ionosphere due to its strong impact on the radio signal propagation. As the most ionized ionospheric region, the F2 layer has the most pronounced effect on transionospheric radio wave propagation. The maximum electron density of the F2 layer, NmF2, and its height, hmF2, are of particular interest for radio communication applications as well as for characterizing the ionosphere. Since these ionospheric key parameters decisively shape the vertical electron density profiles, the precise calculation of them is of crucial importance for an accurate 3‐D electron density reconstruction. The vertical sounding by ionosondes provides the most reliable source of F2 peak measurements. Within this paper, we compare the following data assimilation methods incorporating ionosonde measurements into a background model: Optimal Interpolation (OI), OI with time forecast (OI FC), the Successive Correction Method (SCM), and a modified SCM (MSCM) working with a daytime‐dependent measurement error variance. These approaches are validated with the measurements of nine ionosonde stations for two periods covering quiet and disturbed ionospheric conditions. In particular, for the quiet period, we show that MSCM outperforms the other assimilation methods and allows an accuracy gain up to 75% for NmF2 and 37% for hmF2 compared to the background model. For the disturbed period, OI FC reveals the most promising results with improvements up to 79% for NmF2 and 50% for hmF2 compared to the background and up to 42% for NmF2 and 16% for hmF2 compared to OI.

Wide-area ionospheric delay model for GNSS users in middle- and low-magnetic-latitude regions

A useful ionospheric delay model to compensate for the effect of ionospheric error on GNSS service over continent-wide areas or oceans is the Satellite-Based Augmentation System's wide-area thin-shell planar fit ionospheric grid model. In order to implement a proper wide-area ionospheric delay model in the Asia-Pacific region to reflect the variation introduced by local ionospheric activity, the present study develops a proper ionospheric delay model to correct ionospheric error in middle- and low-magnetic-latitude regions. Specifically, the proposed ionospheric delay model uses several dual-frequency GNSS reference stations distributed in Taiwan, South Korea, Japan, and China as grid points in place of the conventional grid points generated by ionospheric pierce points. The ionospheric delays observed at the reference stations are processed and provided to the user, who can then construct the ionospheric delay model using weighted least squares with the distances between the user and the stations as weights. This proposed ionospheric delay model lowers the computation load by eliminating the conversion of delays at the ionospheric pierce points to those at the grid points and provides good descriptions of dynamic variations due to the ionospheric activities. Also, a simplified model is developed to further reduce its computation load while providing almost the same service as that of the original proposed model. A selection mechanism between the original proposed model and its simplified version is developed as well. The details of the proposed ionospheric delay model are explained, and experiments conducted using data collected from the reference stations in the Asia-Pacific region are presented. The effectiveness of the proposed model is validated by comparison with the conventional wide-area thin-shell planar fit ionospheric grid model provided by the Japanese Multi-functional Satellite Augmentation System under both nominal and disturbed ionospheric conditions.

An Improved Iterative Algorithm for 3-D Ionospheric Tomography Reconstruction

The computerized ionospheric tomography usually involves solving an ill-posed inversion problem. The sparsity of Global Positioning System (GPS) stations and the limitation of projection angles lead to insufficient data acquisition, thereby preventing the accurate reconstruction of ionospheric-electron-density distributions. In this paper, we investigate and propose a 3-D iterative reconstruction algorithm based on the minimization of total variation under quiescent and disturbed ionospheric conditions. Numerical experiments on GPS simulation data and real data are discussed. In contrast to the improved algebraic reconstruction technique, the proposed algorithm exhibits significantly reconstruction accuracy.

Application of hybrid regularization method for tomographic reconstruction of midlatitude ionospheric electron density

Reconstructing ionospheric electron density (IED) is an ill-posed inverse problem, with classical Tikhonov regularization tending to smooth IED structures. By contrast, total variation (TV) regularization effectively resists noise and preserves discontinuities of the IED. In this paper, we regularize the inverse problem by incorporating both Tikhonov and TV regularization. A specific formulation of the proposed method, called hybrid regularization, is introduced and investigated. The method is then tested using simulated data for the actual positions of the GPS satellites and ground receivers, and also applied to the analysis of real observation data under quiescent and disturbed ionospheric conditions. Experiments demonstrate the effectiveness, and illustrate the validity and reliability of the proposed method.

Study of EGNOS safety of life service during the period of solar maximum activity

ABSTRACT The Satellite Base Augmentation System (SBAS) - EGNOS (European Geostationary Navigation Overlay Service) has been certified for Safety of Life (SoL) service for aircraft navigation since 2nd of March 2011. Unfortunately for the territory of Poland, located at the edge of EGNOS service area, the quality of the service corrections are still not sufficient for aircraft navigation requirements. Years 2012 and 2013 are forecasted as a maximum of solar activity in a 11-year solar cycle. This time period will be the chance to perform the first tests for the EGNOS Safety of Life service quality in disturbed ionospheric conditions. During the previous maximum of solar activity, the storm on 30 October 2003 resulted in the inability to use WAAS corrections for more than 12 hours. This was caused by a very large gradient of disturbances and its’ very sharp boundaries - vertical TEC (VTEC) varied from ~ 40 to ~ 120 TECU (TEC units) within an hour (over ~ 150 km distance). These circumstances gave the opportunity to carry out the test flights to examine the navigation parameters obtained for EGNOS SoL service in disturbed ionospheric conditions. The paper presents project proposal of study and analyses of such fundamental navigation parameters as: accuracy of determined position, availability, continuity and integrity, determined for selected disturbances in relation to quiet conditions. It can give a possibility to estimate of the quality of EGNOS SoL service in Polish airspace during the different phases of flight and its resistance to critical ionospheric conditions.

Simulating the impacts of ionospheric scintillation on L band SAR image formation

We develop a phase screen model called the Synthetic Aperture Radar (SAR) Scintillation Simulator (SAR‐SS) for predicting the impacts of ionospheric scintillation on SAR image formation. SAR‐SS consists of a phase screen generator and a propagator. The screen generator creates a 2‐D random realization of spatial phase fluctuations resulting from the traversal of small‐scale field‐aligned irregularities in the ionosphere. It accounts for the motion of the radar platform, the drift of the ionospheric irregularities, and the oblique angle of propagation, all of which determine the scale sizes of the irregularities sampled by the radar beam. The propagator solves the 3‐D parabolic wave equation using the split step technique to compute the ionospheric transfer function for two‐way propagation. This ionospheric transfer function is used to modulate the SAR signal due to terrestrial features in order to assess the ionospheric impact on SAR image formation in the small target approximation. We compare simulated and observed PALSAR imagery over Brazil during disturbed ionospheric conditions. We demonstrate that SAR‐SS can reproduce the field‐aligned streaks in PALSAR imagery caused by irregularities in the equatorial ionosphere that have been observed by previous authors. The field‐aligned streaks exhibited a dominant wavelength larger than the Fresnel break scale, which suggests that refractive scatter was dominant over diffraction as the physical mechanism responsible for the scintillation of the radar signal in this case. The spectral index of phase fluctuations in the screen was quite large (9.0), suggesting that these irregularities were possibly associated with bottomside sinudoidal irregularities rather than equatorial plasma bubbles.

Numerical validations of neural‐network‐based ionospheric tomography for disturbed ionospheric conditions and sparse data

Three‐dimensional ionospheric tomography is effective for investigations of the dynamics of ionospheric phenomena. However, it is an ill‐posed problem in the context of sparse data, and accurate electron density reconstruction is difficult. The Residual Minimization Training Neural Network (RMTNN) tomographic approach, a multilayer neural network trained by minimizing an objective function, allows reconstruction of sparse data. In this study, we validate the reconstruction performance of RMTNN using numerical simulations based on both sufficiently sampled and sparse data. First, we use a simple plasma‐bubble model representing the disturbed ionosphere and evaluate the reconstruction performance based on 40 GPS receivers in Japan. We subsequently apply our approach to a sparse data set obtained from 24 receivers in Indonesia. The reconstructed images from the disturbed and sparse data are consistent with the model data, except below 200 km altitude. To improve this performance and limit any discrepancies, we used information on the electron density in the lower ionosphere. The results suggest the restricted RMTNN‐tomography‐assisted approach is very promising for investigations of ionospheric electron density distributions, including studies of irregular structures in different regions. In particular, RMTNN constrained by low‐Earth‐orbit satellite data is effective in improving the reconstruction accuracy.