Computerized Ionospheric Tomography Research Articles

IONOLAB-Fusion: Fusion of Radio Occultation into Computerized Ionospheric Tomography

In this study, a 4-D, computerized ionospheric tomography algorithm, IONOLAB-Fusion, is developed to reconstruct electron density using both actual and virtual vertical and horizontal paths for all ionospheric states. The user-friendly algorithm only requires the coordinates of the region of interest and range with the desired spatio-temporal resolutions. The model ionosphere is formed using spherical voxels in a lexicographical order so that a 4-D ionosphere can be mapped to a 2-D matrix. The model matrix is formed automatically using a background ionospheric model with an optimized retrospective or near-real time manner. The singular value decomposition is applied to extract a subset of significant singular values and corresponding signal subspace basis vectors. The measurement vector is filled automatically with the optimized number of ground-based and space-based paths. The reconstruction is obtained in closed form in the least squares sense. When the performance of IONOLAB-Fusion across Europe was compared with ionosonde profiles, a 26.51% and 32.33% improvement was observed over the background ionospheric model for quiet and disturbed days, respectively. When compared with GIM-TEC, the agreement of IONOLAB-Fusion was 37.89% and 31.58% better than those achieved with the background model for quiet and disturbed days, respectively.

Global Three‐Dimensional Ionospheric Tomography by Combination of Ground‐Based and Space‐Borne GNSS Data

AbstractThe inhomogeneous distribution of Global Navigation Satellite System (GNSS) data is a significant problem for global GNSS computerized ionospheric tomography (CIT). By combining ground‐based GNSS data from 460 global stations with space‐borne GNSS data onboard eleven Low‐Earth‐Orbit (LEO) satellites, we employed the EOF (empirical orthogonal function)‐based multiplicative algebraic reconstruction technique (EMART) to reconstruct the global ionospheric electron densities. In comparison with GNSS + LEO (EMART_GL) solutions, the proportion of crossed voxels for GNSS‐only (EMART_G) solutions can rise by up to 12.54%, from 56.83% to 69.37%. Validation experiments were conducted under quiet and disturbed conditions using GNSS slant total electron content (STEC) references that were not previously used in ionospheric tomography. The EMART_GL solutions outperformed the EMART_G solutions when compared to the STEC references under quiet and disturbed conditions. The root mean square values of the CIT‐derived STEC for the EMART_G solutions can be decreased by 31.3% and 30.3% on average under quiet and disturbed conditions, respectively. The vertical TEC references from the Jason‐2 satellite were also used for validation over the ocean areas. Due to insufficient data over the ocean areas, the EMART_GL solutions showed no significant improvements. The reconstructed 3D IEDs were further validated with the COSMIC electron density profiles. Generally, the tomographic results of the EMART_GL solutions were more consistent with the COSMIC profiles when compared to those of the EMART_G solutions and the NeQuick‐2 model. It demonstrates that it is beneficial for global ionospheric tomography by combining ground‐based and space‐borne data.

3-D Computerized Ionospheric Tomography With GPS, SAR, and Ionosonde

The GPS-based computerized ionospheric tomography (CIT) has the capacity to reconstruct the three-dimensional ionosphere (i.e., electron density distribution), making it one of the most important techniques for ionospheric observation. However, the CIT technology is unable of high vertical resolution due to the restricted viewing angle. Therefore, the precision of CIT cannot be substantially enhanced with GPS only. Aiming at this issue, this paper proposes a bi-iteration algorithm that integrates GPS, Phased Array L-band Synthetic Aperture Radar on board the Advanced Land Observing Satellite (ALOS PALSAR), and ionosonde data. The key is that the joint retrieval of PALSAR and ionosonde may offer high-precision one-dimensional electron density profile along the whole path, which can effectively enhance the authenticity of the iterative initial value. The corrected initial value is then fused into the process of CIT, which can finally improve the precision of vertical resolution after two iterations. Experimental verification demonstrates that due to the ability to obtain more realistic initial values, the reconstruction accuracy of the algorithm proposed in this paper is 51.4 percent and 45.1 percent higher than the accuracy with GPS alone and with GPS and ionosonde data, respectively. This indicates that the combination of these three kinds of data can effectively improve the precision of CIT.

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 Reconstruction Using GNSS Signals Around an Anomaly Crest Location in Indian Longitude Sector

AbstractThe present study aims to reconstruct the vertical ionospheric electron density (IED) profile using computerized ionospheric tomography (CIT) techniques, over the northern crest of the equatorial ionization anomaly (EIA) which is one of the most geo‐physically sensitive regions of Indian longitude sector. Total electron content (TEC) measurements obtained from GNSS signals from receivers located at Kolkata (22.57°N, 88.36°E), Purulia (23.33°N, 86.36°E), and Siliguri (26.73°N, 88.39°E) and International GNSS Service (IGS) stations of Port Blair (11.64°N, 92.71°E), Bangalore (13.02°N, 77.57°E), Hyderabad (17.42°N, 78.55°E), Lucknow (26.91°N, 80.96°E) and Lhasa (29.66°N, 91.10°E) have been incorporated into the tomography algorithm for ionospheric reconstructions. Among the different iterative techniques used for retrieving IED profiles on a 2‐dimensional altitude versus latitude plane fixed at a certain longitude, simultaneous iterative reconstruction technique (SIRT) was shown to be the optimum choice based on the representation of the EIA phenomenon and reconstruction accuracy. A comparative assessment between two ionospheric models IRI2016 and PIM1.4 was performed, with PIM based initial guess for inversions resulting in lower reconstruction errors. The 2D CIT algorithm was then used to reconstruct the hourly vertical IED profiles to study the impact of the severe G4‐class St. Patrick's Day storm on 17 March 2015 and reconstructed electron densities showed a large increase over the values obtained from the geomagnetically quiet day of 10 March 2015, indicating a positive ionospheric storm phase. Ionospheric response to the G1‐class geomagnetic disturbance on 5 December 2017 and the average F‐region IED values have also been compared with a geomagnetically quiet day of 3 December 2017.

Sparse Reconstruction of 3-D Regional Ionospheric Tomography Using Data From a Network of GNSS Reference Stations

3-D computerized ionospheric tomography (CIT) is an ill-posed problem due to the insufficient amount of observations, it remains challenging for practical applications. In this article, we proposed an ionospheric tomography method that combined data-driven methods with compressed sensing (CS) to deal with the ill-posed problem. First, slant total electron content (STEC) data were extracted by undifferenced and uncombined precise point positioning (UCPPP) with known fixed station coordinates. Second, data-driven methods were adopted to construct the projection matrix from the ionospheric model. Third, compressed sensing was used to derive the sparse solution based on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula> norm. The ionospheric tomography can be achieved well by using observations during the shorter time interval and in a sparse receiver distribution based on the property of compressed sensing. Results of experiment based on real Global Positioning System (GPS) observation data verified the effectiveness of the proposed methods. By comparing with the colocated ionosonde, it is found that the CS methods are more consistent with the actual ionospheric fluctuation than the modified constrained algebraic reconstruction technique (CART). In terms of the differential STEC (dSTEC) analysis, the error of the tomography model by Compressed Sensing-Principal Component Analysis (CS-PCA) is less than 0.2 TEC unit (TECU), and the time resolution is 5 min. The UCPPP with constraint by CS-PCA shows the best performance of 12.2%, 40.9% and 0.31% improvement in positioning accuracy, convergence time, and fixed rate over the UCPPP with constraint by modified CART. The proposed data-driven methods may be important for high-resolution 4-D ionospheric tomography in the future.

High‐Resolution 3‐D Imaging of Daytime Sporadic‐E Over Japan by Using GNSS TEC and Ionosondes

AbstractA novel two‐step three‐dimensional (3‐D) computerized ionospheric tomography (CIT) technique has been developed to image the structure of daytime midlatitude sporadic‐E (Es). The CIT relies on total electron content (TEC) from a dense ground‐based Global Navigation Satellite System (GNSS) receiver network over the Japan area. First, on a coarse grid, the TEC data and a multiplicative algebraic reconstruction technique (MART) are used to reconstruct the F region from a smooth background. Then, on a fine grid and using singular value decomposition (SVD), the residues after deducting the F region contribution to TEC are utilized in reconstructing the E region, extending 80–180 km in altitude. To vertically constrain the E region solution, we introduced a family of subsets of time‐dependent empirical orthogonal functions (EOFs) from a Chapman model function tuned to manually scaled ionosonde observations. We analyzed three event days to validate the results. East‐West (E‐W) aligned frontal structures, spanning several hundred kilometers, migrating northward in the morning and southward in the afternoon, were observed. The new technique effectively tracks the Es‐height variation over time, which had proved difficult to reproduce in earlier tempts at 3‐D Es reconstructions.

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

Ionized by solar radiation, the ionosphere causes a phase rotation or time delay to trans-ionospheric radio waves. Reconstruction of ionospheric electron density profiles with global navigation satellite system (GNSS) observations has become an indispensable technique for various purposes ranging from space physics studies to radio applications. This paper conducts a comprehensive review on the development of voxel-based computerized ionospheric tomography (CIT) in the last 30 years. A brief introduction is given in chronological order starting from the first report of CIT with simulation to the newly proposed voxel-based algorithms for ionospheric event analysis. The statement of the tomographic geometry and voxel models are outlined with the ill-posed and ill-conditioned nature of CIT addressed. With the additional information from other instrumental observations or initial models supplemented to make the coefficient matrix less ill-conditioned, equation constructions are categorized into constraints, virtual data assimilation and multi-source observation fusion. Then, the paper classifies and assesses the voxel-based CIT algorithms of the algebraic method, statistical approach and artificial neural networks for equation solving or electron density estimation. The advantages and limitations of the algorithms are also pointed out. Moreover, the paper illustrates the representative height profiles and two-dimensional images of ionospheric electron densities from CIT. Ionospheric disturbances studied with CIT are presented. It also demonstrates how the CIT benefits ionospheric correction and ionospheric monitoring. Finally, some suggestions are provided for further research about voxel-based CIT.

Complementing regional ground GNSS-STEC computerized ionospheric tomography (CIT) with ionosonde data assimilation

A near-real-time computerized ionospheric tomography (CIT) technique was developed over the East Asian sector to specify the 3-D electron density field. The technique is based on a plethora of Global Navigation Satellite System observables within the region of interest which is bounded horizontally 110°–160°E and 10°–60°N and extending from 80 to 25,000 km in altitude. Prior to deployment, studies validated the CIT results using ionosonde, middle-upper atmosphere radar and occultation data and found the technique to adequately reconstruct the regional ionosphere vertical structure. However, with room for improvement in estimating the peak height and avoiding physically unrealistic negative densities in the final solution, we present preliminary results from a technique that addresses these issues by incorporating CIT results into a data assimilation (DA) technique. The DA technique adds ionosonde bottomside measurements into CIT results, thereby improving the accuracy of the reconstructed bottomside 3-D structure. More specifically, on average CIT NmF2 and hmF2 improve by more than 60%. Further, during analysis, ionospheric electron densities are assumed to be better described by probability log-normal distribution, which introduces the positivity constraint that is mandatory in ionospheric imaging.

Multi-Scale Ionospheric Anomalies Monitoring and Spatio-Temporal Analysis during Intense Storm

The ionosphere is a significant component of the geospace environment. Storm-induced ionospheric anomalies severely affect the performance of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT) and human space activities, e.g., the Earth observation, deep space exploration, and space weather monitoring and prediction. In this study, we present and discuss the multi-scale ionospheric anomalies monitoring over China using the GNSS observations from the Crustal Movement Observation Network of China (CMONOC) during the 2015 St. Patrick’s Day storm. Total Electron Content (TEC), Ionospheric Electron Density (IED), and the ionospheric disturbance index are used to monitor the storm-induced ionospheric anomalies. This study finally reveals the occurrence of the large-scale ionospheric storms and small-scale ionospheric scintillation during the storm. The results show that this magnetic storm was accompanied by a positive phase and a negative phase ionospheric storm. At the beginning of the main phase of the magnetic storm, both TEC and IED were significantly enhanced. There was long-duration depletion in the topside ionospheric TEC during the recovery phase of the storm. This study also reveals the response and variations in regional ionosphere scintillation. The Rate of the TEC Index (ROTI) was exploited to investigate the ionospheric scintillation and compared with the temporal dynamics of vertical TEC. The analysis of the ROTI proved these storm-induced TEC depletions, which suppressed the occurrence of the ionospheric scintillation. To improve the spatial resolution for ionospheric anomalies monitoring, the regional Three-Dimensional (3D) ionospheric model is reconstructed by the Computerized Ionospheric Tomography (CIT) technique. The spatial-temporal dynamics of ionospheric anomalies during the severe geomagnetic storm was reflected in detail. The IED varied with latitude and altitude dramatically; the maximum IED decreased, and the area where IEDs were maximum moved southward.

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 response to the 17 March and 22 June 2015 geomagnetic storms over Wuhan region using GNSS-based tomographic technique

By using the data of GNSS (Global Navigation Satellite System) observation from Crustal Movement Observation Network of China (CMONOC), ionospheric electron density (IED) distributions reconstructed by using computerized ionospheric tomography (CIT) technique are used to investigate the ionospheric storm effects over Wuhan region during 17 March and 22 June 2015 geomagnetic storm periods. F-region critical frequency (foF2) at Wuhan ionosonde station shows an obvious decrease during recovery phase of the St. Patrick’s Day geomagnetic storm. Moreover, tomographic results present that the decrease in electron density begins at 12:00 UT on 17 March during the storm main phase. Also, foF2 shows a long-lasting negative storm effect during the recovery phase of the 22 June 2015 geomagnetic storm. Electron density chromatography presents the evident decrease during the storm day in accordance with the ionosonde observation. These ionospheric negative storm effects are probably associated with changes of chemical composition, PPEF and DDEF from high latitudes.

Virtual reference station-based computerized ionospheric tomography

In computerized ionospheric tomography (CIT) with ground-based GNSS, the voxels without satellite-receiver ray traversing cannot be reconstructed directly. We present a CIT algorithm based on virtual reference stations (VRSs), called VRS–CIT, to decrease the number of unilluminated voxels and improve the precision of the estimated ionospheric electron density (IED). The VRSs are set at the nodes of grids with a 0.5° × 0.5° resolution in longitude and latitude. We generate the virtual observations with the observations from nearby six or three stations selected according to azimuths and distances. The generation utilizes multi-quadric surface fitting with six stations and triangular linear interpolation with three stations. With the virtual observations added, the IED distribution is reconstructed by the multiplicative algebraic reconstruction technique with the initial values obtained from IRI-2016. The performance of VRS–CIT is examined by using the data from 127 GNSS stations located in 24–46° N and 122–146° E to derive the IED every 30 min. The study focuses on April 29, 2014, with the adaptability of VRS–CIT analyzed by 12 days, evenly distributed around equinoxes and solstices of 2014. The accuracy of the virtual observation is about 1 TECU. Comparing to that derived from CIT with only real observations, the unsolvability of VRS–CIT declined by 4–12% for the whole region, and for the main area, the improvement can be up to 70%. Taking two IED profiles from radio occultation as reference measurements, the mean absolute error (MAE) of IED by VRS–CIT decreases by 6.88% and 8.43%, respectively. Comparing with slant total electron content (STEC) extracted from five additional GNSS stations, the MAE and the root mean square error of the estimated STEC can be reduced up to 17.24% and 33.81%, respectively.

An Improved Computerized Ionospheric Tomography Model Fusing 3-D Multisource Ionospheric Data Enabled Quantifying the Evolution of Magnetic Storm

Global Navigation Satellite System (GNSS) ionospheric tomography is a typical ill-posed problem. Joint inversion with external observation data is one of the effective ways to mitigate the problem. In this article, by fusing 3-D multisource ionospheric data, and improving the stochastic model, an improved GNSS tomographic algorithm MFCIT [computerized ionospheric tomography (CIT) using mapping function] is presented. The accuracy of the algorithm is validated by selected data under different geomagnetic and solar conditions acquired in Europe. The results show that the estimated, statistically significant uncertainty for each of the layers is about 0.50–3.0TECU, with the largest absolute error within 6.0TECU. The advantage of the MFCIT is that it is based on the Kalman filter, which enables efficient near real-time 3-D monitoring of ionosphere. The temporal resolution can reach ~1 min level. Here, we apply the ionospheric tomography inversion to the magnetic storm on January 7, 2015, in the European region, and quantified the evolution of the storm. The results show that the difference of the core region between the MFCIT and CODE GIM is less than 1TECU. More importantly, during the initial phase of the storm, when the ionospheric disturbance is not evident in the single layer CODE GIM model, the MFCIT shows obvious positive disturbances in the upper ionosphere, although there is no disturbance in the F2 layer. The MFCIT further tracks the evolution of the magnetic storm that the ionospheric disturbance expands from the upper to the lower ionosphere layers, and at UT12:00, the disturbance continues to spread to the F2 layer.

3D ionospheric tomography over southeast China using a new scheme of constrained least squares with parameter weight matrix

Computerized ionospheric tomography (CIT) technique allows reconstructing the 3-dimensional and even 4-dimensional state of the ionosphere in terms of electron content. It is typically denoted as an inverse problem. Due to the unevenly distributed measurements collected from ground receivers, together with limited cut-off elevation angle and density of observations, the normal matrix of the inverse problem becomes sparse, which makes it difficult to solve and potentially unstable. The main methods to resolve the problem are the constraint algorithms during the process of the electron density inversion. A new approach is proposed for CIT that aims to mitigate the ill-posed problem and improve the precision of ionospheric electron density (IED) resolution by using constrained least squares. In this method, a new scheme of constructing parameter weight matrices in both horizontal and vertical directions is designed using the correlation of IED among those neighboring voxels, which helps to add the information needed in CIT, and the ill-posed problem is efficiently resolved. The accuracy and feasibility of the additional constraints in CIT algorithms are verified by numerical simulation tests. Finally, this newly developed method of constrained least squares is used to effectively perform the tomographic reconstruction of IED distribution over southeast China.

Reconstruction of 2D/3D ionospheric disturbances in high-latitude and arctic regions during a geomagnetic storm using GNSS carrier TEC: a case study of the 2015 great storm

On 2015 March, a G4-level geomagnetic storm hit the earth and then triggered global ionospheric disturbances. A considerable number of studies have been published showing various ionospheric responses in low- and mid-latitude regions. In contrary, very limited efforts have been made on high-latitude or polar regions. Therefore, this paper reconstructed and investigated the 2D/3D ionospheric disturbances in high-latitude and arctic regions during this great storm using multiprocessing methods. First, four longitudinal global navigation satellite system stations’ sectors are selected on Polar area, and the second-order differential of total electron content (dTEC) of each sectors is calculated to detect the ionosphere anomaly during the time of interests. Compared with the “auroral oval” distribution and the precipitating of auroral electrons data from Defense Meteorological Satellite Program, the triggering mechanism of the detected anomaly is discussed. Second, based on the dTEC detection results and the auroral electrojet index series, two disturbances processes have been identified. Then, a new computerized ionospheric tomography (CIT) algorithm called MFCIT (CIT with mapping function) is introduced, and the 3D ionosphere images under daytime (LT06:00–LT06:30) and nighttime (LT21:00–LT22:00) over Alaska are individually inverted at the temporal resolution of 1 min. In contrast with magnetic field lines distribution, the relationship between disturbances and geomagnetic fields has been analyzed. Last, two vertical electron motions are monitored with the CIT images. As the two motions occur at two different steps of the geomagnetic storm, the characteristics and amplitudes of the vertical movements can be distinguished. The physical mechanisms for the vertical motions are discussed. The upward vertical motion during the first disturbance may be induced by the eastward abnormal penetration electric field, while the second disturbance may be the outcome of the combined influences of the abnormal electric field and the precipitating of auroral electrons.

3-D ionospheric tomography from dense GNSS observations based on an improved two-step iterative algorithm

Computerized ionospheric tomography (CIT) can image 3-D ionospheric variations from ground Global Navigation Satellite System (GNSS) observations. However, due to the sparse and inhomogeneous ground GNSS observations, the prior information from the empirical models (e.g., IRI-2012 and NeQuick 2) have to be used, which affect the reconstructed results in the CIT, particularly the peak parameters of the F2 layer, namely foF2 and M(3000)F2. In this paper, an improved two-step CIT algorithm is developed to image the ionospheric electron density (IED) distribution up to 2000 km over Japan using dense GNSS Earth Observation Network (GEONET) observations operated by the Geospatial Information Authority (GSI) of Japan. Firstly, we update the IRI-2012 using the ground-based GNSS observations. The NeQuick-2 is used to provide the vertical ionospheric profile, and foF2 and M(3000)F2 derived from CCIR model in NeQuick 2 are improved by the B-spline modeling methods. Secondly, the updated IRI-2012 is input as a prior value and the multiplicative algebraic reconstruction technique (MART) is implemented to reconstruct the IED distribution. The reconstructed results are validated by the simulation and observation results from ground-based GNSS, GNSS Radio Occultation (GNSS-RO) observations and ionosonde measurements. The results demonstrate the feasibility and superiority of our new method. The standard deviations of TEC residual errors from the updated NeQuick 2 are at least 20% less than those from the original NeQuick 2 model, and the updated NeQuick 2 has better performance for the ionospheric correction.

Preliminary observation results of the Coherent Beacon System onboard the China Seismo-Electromagnetic Satellite-1

This paper reports, for the first time, observation results of the Coherent Beacon System (CBS) onboard the China Seismo-Electromagnetic Satellite-1 (CSES-1). We describe the CBS, and the Computerized Ionospheric Tomography (CIT) algorithm program is validated by numerical experiment. Two examples are shown, for daytime and nighttime respectively. The Equatorial Ionization Anomaly (EIA) can be seen, and the northern crest core is located at ~20°N in the reconstruction image at 07:28 UTC on 20 July 2018 (daytime). Disturbances are shown in the reconstruction image at 18:40 UTC on 13 July 2018 (nighttime). We find that beacon measurements are more consistent with ionosonde measurements than model results, by comparing NmF2 at three sites at Lanzhou, Chongqing, and Kunming; consistency with ionosonde measurements validates beacon measurements. Finally, we have studied Vertical Total Electron Content (VTEC) variations from ground to ~500 km (the height of CSES-1 orbit) and ratios of VTEC between beacon measurements and CODE (Center for Orbit Determination in Europe) data. VTEC variation from ground to ~500 km has a range of 7.2–16.5 TECU for the daytime case and a range of 1.1–1.7 TECU for the nighttime case. The Beacon/CODE ratio of VTEC varies with latitude and time. The mean Beacon/CODE ratio is 0.69 for the daytime case and 0.26 for the nighttime case. The fact that the nighttime case yields lower ratios indicates the higher altitude of the ionosphere during nighttime when the ionosphere is assumed to be a thin layer.

Ionospheric Reconstructions Using Faraday Rotation in Spaceborne Polarimetric SAR Data

It is well known that the Faraday rotation (FR) is obviously embedded in spaceborne polarimetric synthetic aperture radar (PolSAR) data at L-band and lower frequencies. By model inversion, some widely used FR angle estimators have been proposed for compensation and provide a new field in high-resolution ionospheric soundings. However, as an integrated product of electron density and the parallel component of the magnetic field, FR angle measurements/observations demonstrate the ability to characterize horizontal ionosphere. In order to make a general study of ionospheric structure, this paper reconstructs the electron density distribution based on a modified two-dimensional computerized ionospheric tomography (CIT) technique, where the FR angles, rather than the total electron content (TEC), are regarded as the input. By using the full-pol (full polarimetric) data of Phase Array L-band Synthetic Aperture Radar (PALSAR) on board Advanced Land Observing Satellite (ALOS), International Reference Ionosphere (IRI) and International Geomagnetic Reference Field (IGRF) models, numerical simulations corresponding to different FR estimators and SAR scenes are made to validate the proposed technique. In simulations, the imaging of kilometer-scale ionospheric disturbances, a spatial scale that is rarely detectable by CIT using GPS, is presented. In addition, the ionospheric reconstruction using SAR polarimetric information does not require strong point targets within a SAR scene, which is necessary for CIT using SAR imaging information. Finally, the effects of system errors including noise, channel imbalance and crosstalk on the reconstruction results are also analyzed to show the applicability of CIT based on spaceborne full-pol SAR data.

Robust Computerized Ionospheric Tomography Based on Spaceborne Polarimetric SAR Data

Due to the dispersion nature of the ionosphere, the spaceborne polarimetric synthetic aperture radar (PolSAR) systems at L or lower frequencies will generally experience more severe effects in comparison to frequencies above L-band. Correspondingly, according to the mechanism of how ionosphere destroys the scattering matrix of PolSAR data, the total electron content (TEC), an important input in computerized ionospheric tomography (CIT), can be retrieved by model inversion. Thus, this paper presents a technique of CIT based on the spaceborne PolSAR data. The CIT technique is a means to obtain the spatial distribution of ionospheric electron density from the TEC values. Because of the high spatial resolution of spaceborne SAR, the kilometer-scale TEC information can be obtained by the PolSAR data where such resolution was previously inaccessible. The spatial distribution of ionospheric electron density with high resolution can therefore be obtained. In addition, the potential limitation of previous CIT based on SAR imaging information is the difficulty in requiring strong point targets with high signal-to-clutter (SCR) ratio in scenes. In contrast, the CIT reconstruction based on scattering matrix information can be easily realized without aforementioned special requirements. In this paper, by using the simulated data of the Advanced Land Observing Satellite (ALOS) Phased-Array L-band Synthetic Aperture Radar (PALSAR) full-pol data, the International Reference Ionosphere (IRI) 2007, and the International Geomagnetic Reference Field (IGRF) models, the reconstruction of ionospheric electron density distribution is first simulated to validate the feasibility of the proposed technique. Then, possible effects of SAR system and model errors on the reconstruction results are also simulated and analyzed to show the applicability.