scholarly journals Virtual reference station-based computerized ionospheric tomography

GPS Solutions ◽  
2020 ◽  
Vol 25 (1) ◽  
Author(s):  
Weijun Lu ◽  
Guanyi Ma ◽  
Qingtao Wan ◽  
Jinghua Li ◽  
Xiaolan Wang ◽  
...  
Keyword(s):  
Absolute Error ◽  
Linear Interpolation ◽  
Reference Station ◽  
Reconstruction Technique ◽  
Electron Content ◽  
Multiplicative Algebraic Reconstruction Technique ◽  
Virtual Reference ◽  
Total Electron ◽  
Ionospheric Tomography ◽  
Computerized Ionospheric Tomography

Abstract 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.

scholarly journals Reconstruction of Storm‐Time Total Electron Content Using Ionospheric Tomography and Artificial Neural Networks: A Comparative Study Over the African Region

Radio Science ◽  
2018 ◽  
Vol 53 (11) ◽  
pp. 1328-1345 ◽  
Author(s):  
Jean Claude Uwamahoro ◽  
Nigussie M. Giday ◽  
John Bosco Habarulema ◽  
Zama T. Katamzi‐Joseph ◽  
Gopi Krishna Seemala
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Comparative Study ◽  
Total Electron Content ◽  
Electron Content ◽  
African Region ◽  
Total Electron ◽  
Ionospheric Tomography ◽  
Artificial Neural

scholarly journals Application of generalized singular value decomposition to ionospheric tomography

2004 ◽  
Vol 22 (10) ◽  
pp. 3437-3444 ◽  
Author(s):  
K. Bhuyan ◽  
S. B. Singh ◽  
P. K. Bhuyan
Keyword(s):  
Singular Value Decomposition ◽  
Regularization Parameter ◽  
Singular Value ◽  
Electron Content ◽  
Generalized Singular Value Decomposition ◽  
Total Electron ◽  
Ionospheric Tomography ◽  
Low Latitude Ionosphere ◽  
A Chain ◽  
Value Decomposition

Abstract. The electron density distribution of the low- and mid-latitude ionosphere has been investigated by the computerized tomography technique using a Generalized Singular Value Decomposition (GSVD) based algorithm. Model ionospheric total electron content (TEC) data obtained from the International Reference Ionosphere 2001 and slant relative TEC data measured at a chain of three stations receiving transit satellite transmissions in Alaska, USA are used in this analysis. The issue of optimum efficiency of the GSVD algorithm in the reconstruction of ionospheric structures is being addressed through simulation of the equatorial ionization anomaly (EIA), in addition to its application to investigate complicated ionospheric density irregularities. Results show that the Generalized Cross Validation approach to find the regularization parameter and the corresponding solution gives a very good reconstructed image of the low-latitude ionosphere and the EIA within it. Provided that some minimum norm is fulfilled, the GSVD solution is found to be least affected by considerations, such as pixel size and number of ray paths. The method has also been used to investigate the behaviour of the mid-latitude ionosphere under magnetically quiet and disturbed conditions.

scholarly journals DETECTION OF EQUATORIAL PLASMA BUBBLES USING GPS IONOSPHERIC TOMOGRAPHY OVER PENINSULAR MALAYSIA

2021 ◽  
Vol 6 (24) ◽  
pp. 152-160
Author(s):  
Siti Syukriah Khamdan ◽  
Tajul Ariffin Musa ◽  
Suhaila M. Buhari
Keyword(s):  
Three Dimensional ◽  
Peninsular Malaysia ◽  
Rate Of Change ◽  
Electron Content ◽  
Total Electron ◽  
Ionospheric Tomography ◽  
Plasma Bubbles ◽  
Equatorial Plasma Bubbles ◽  
Tomography Method

This paper presents the detection of the equatorial plasma bubbles (EPB) using the Global Positioning System (GPS) ionospheric tomography method over Peninsular Malaysia. This paper aims to investigate the capability of the GPS ionospheric tomography method in detecting the variations of the EPB over the study area. In doing so, a previous case study during post-sunset 5th April 2011 has been selected as a reference for the detection of the EPBs over the study area. It has been observed that at least three structures of the EPBs have been captured based on the rate of change total electron content (TEC) index (ROTI) from 12 UT until 19 UT. Therefore, the three-dimensional ionospheric profiles have been reconstructed over Peninsular Malaysia using the tomography method during the study period in order to capture the signature of the EPBs. In this study, the detection of the EPBs using the tomography method is based on the rate of change of electron density (ROTNe). The results from three-dimensional ionospheric tomography show only two structures of EPBs are detected during the study period. It has been observed that the ROTNe depleted up to ~-12x109el/cm. Overall, the results in this study show that the GPS ionospheric tomography capable to be utilized in detecting the variations of EPBs in support of ionospheric studies and monitoring in the Malaysian region.

scholarly journals Using sparse regularization for multi-resolution tomography of the ionosphere

2015 ◽  
Vol 22 (5) ◽  
pp. 613-624 ◽  
Author(s):  
T. Panicciari ◽  
N. D. Smith ◽  
C. N. Mitchell ◽  
F. Da Dalt ◽  
P. S. J. Spencer
Keyword(s):  
Basis Functions ◽  
Compact Representation ◽  
Electron Content ◽  
Wavelet Basis ◽  
Sparse Regularization ◽  
Total Electron ◽  
Localization Property ◽  
Minimization Algorithms ◽  
Minimization Technique ◽  
Computerized Ionospheric Tomography

Abstract. Computerized ionospheric tomography (CIT) is a technique that allows reconstructing the state of the ionosphere in terms of electron content from a set of slant total electron content (STEC) measurements. It is usually denoted as an inverse problem. In this experiment, the measurements are considered coming from the phase of the GPS signal and, therefore, affected by bias. For this reason the STEC cannot be considered in absolute terms but rather in relative terms. Measurements are collected from receivers not evenly distributed in space and together with limitations such as angle and density of the observations, they are the cause of instability in the operation of inversion. Furthermore, the ionosphere is a dynamic medium whose processes are continuously changing in time and space. This can affect CIT by limiting the accuracy in resolving structures and the processes that describe the ionosphere. Some inversion techniques are based on ℓ2 minimization algorithms (i.e. Tikhonov regularization) and a standard approach is implemented here using spherical harmonics as a reference to compare the new method. A new approach is proposed for CIT that aims to permit sparsity in the reconstruction coefficients by using wavelet basis functions. It is based on the ℓ1 minimization technique and wavelet basis functions due to their properties of compact representation. The ℓ1 minimization is selected because it can optimize the result with an uneven distribution of observations by exploiting the localization property of wavelets. Also illustrated is how the inter-frequency biases on the STEC are calibrated within the operation of inversion, and this is used as a way for evaluating the accuracy of the method. The technique is demonstrated using a simulation, showing the advantage of ℓ1 minimization to estimate the coefficients over the ℓ2 minimization. This is in particular true for an uneven observation geometry and especially for multi-resolution CIT.

scholarly journals Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter

2020 ◽  
Vol 12 (6) ◽  
pp. 951 ◽  
Author(s):  
Liangliang Yuan ◽  
Shuanggen Jin ◽  
Mainul Hoque
Keyword(s):  
Selection Procedure ◽  
Global Navigation Satellite Systems ◽  
Reference Station ◽  
Electron Content ◽  
Recursive Method ◽  
Total Electron ◽  
Recursive Filter ◽  
Satellite Systems ◽  
Ionospheric Modeling ◽  
Reference Selection

The differential code bias (DCB) of the Global Navigation Satellite Systems (GNSS) receiver should be precisely corrected when conducting ionospheric remote sensing and precise point positioning. The DCBs can usually be estimated by the ground GNSS network based on the parameterization of the global ionosphere together with the global ionospheric map (GIM). In order to reduce the spatial-temporal complexities, various algorithms based on GIM and local ionospheric modeling are conducted, but rely on station selection. In this paper, we present a recursive method to estimate the DCBs of Global Positioning System (GPS) satellites based on a recursive filter and independent reference station selection procedure. The satellite and receiver DCBs are estimated once per local day and aligned with the DCB product provided by the Center for Orbit Determination in Europe (CODE). From the statistical analysis with CODE DCB products, the results show that the accuracy of GPS satellite DCB estimates obtained by the recursive method can reach about 0.10 ns under solar quiet condition. The influence of stations with bad performances on DCB estimation can be reduced through the independent iterative reference selection. The accuracy of local ionospheric modeling based on recursive filter is less than 2 Total Electron Content Unit (TECU) in the monthly median sense. The performance of the recursive method is also evaluated under different solar conditions and the results show that the local ionospheric modeling is sensitive to solar conditions. Moreover, the recursive method has the potential to be implemented in the near real-time DCB estimation and GNSS data quality check.

scholarly journals Sodankylä ionospheric tomography dataset 2003–2014

2015 ◽  
Vol 5 (2) ◽  
pp. 385-404
Author(s):  
J. Norberg ◽  
L. Roininen ◽  
A. Kero ◽  
T. Raita ◽  
T. Ulich ◽  
...  
Keyword(s):  
Total Electron Content ◽  
Low Earth Orbit ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Dual Frequency ◽  
Total Electron ◽  
Ionospheric Tomography ◽  
Maximum Elevation ◽  
Long Term Performance ◽  
Term Performance

Abstract. Sodankylä Geophysical Observatory has been operating a tomographic receiver network and collecting the produced data since 2003. The collected dataset consists of phase difference curves measured from Russian COSMOS dual-frequency (150/400 MHz) low-Earth-orbit satellite signals, and tomographic electron density reconstructions obtained from these measurements. In this study vertical total electron content (VTEC) values are integrated from the reconstructed electron densities to make a qualitative and quantitative analysis to validate the long-term performance of the tomographic system. During the observation period, 2003–2014, there were three-to-five operational stations at the Fenno-Scandinavian sector. Altogether the analysis consists of around 66 000 overflights, but to ensure the quality of the reconstructions, the examination is limited to cases with descending (north to south) overflights and maximum elevation over 60°. These constraints limit the number of overflights to around 10 000. Based on this dataset, one solar cycle of ionospheric vertical total electron content estimates is constructed. The measurements are compared against International Reference Ionosphere IRI-2012 model, F10.7 solar flux index and sunspot number data. Qualitatively the tomographic VTEC estimate corresponds to reference data very well, but the IRI-2012 model are on average 40 % higher of that of the tomographic results.

scholarly journals An improved method using adaptive smoothing for GNSS tomographic imaging of ionosphere

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250613
Author(s):  
Rushang Jia ◽  
Xumin Yu ◽  
Jianping Xing ◽  
Yafei Ning ◽  
Hecheng Sun
Keyword(s):  
A Priori ◽  
Simulated Data ◽  
Reconstruction Technique ◽  
Electron Content ◽  
Observation Data ◽  
A Priori Information ◽  
Improved Method ◽  
Adaptive Smoothing ◽  
Total Electron ◽  
Priori Information

Global navigation satellite system (GNSS) is a well-established sensors in the recent ionosphere research. By comparing with classical meteorological equipments, the GNSS application can obtain more reliable and precious ionospheric total electron content (TEC) result. However, the most used GNSS ionospheric tomography technique is sensitive to a priori information due to the sparse and non-uniform distribution of GNSS stations. In this paper, we propose an improved method based on adaptive Laplacian smoothing and algebraic reconstruction technique (ALS-ART). Compared with traditional constant constraints, this method is less dependent on a priori information and adaptive smoothing constraints is closer to the actual situation. Tomography experiments using simulated data show that reconstruction accuracy of ionospheric electron density using ALS-ART method is significantly improved. We also use the method to do the analysis of real observation data and compare the tomography results with ionosonde observation data. The results demonstrate the superiority and reliability of the proposed method compared to traditional constant constraints method which will further improve the capability of obtaining precious ionosphere TEC by using GNSS.

scholarly journals Comparison of quiet-time ionospheric total electron content from the IRI-2016 model and from gridded and station-level GPS observations

2020 ◽  
Vol 38 (3) ◽  
pp. 725-748
Author(s):  
Gizaw Mengistu Tsidu ◽  
Mulugeta Melaku Zegeye
Keyword(s):  
Total Electron Content ◽  
Local Time ◽  
Zenith Angle ◽  
Solar Zenith Angle ◽  
Mean Absolute Error ◽  
Model Performance ◽  
Absolute Error ◽  
Electron Content ◽  
Total Electron ◽  
The Difference

Abstract. Earth's ionosphere is an important medium of radio wave propagation in modern times. However, the effective use of the ionosphere depends on the understanding of its spatiotemporal variability. Towards this end, a number of ground- and space-based monitoring facilities have been set up over the years. The information from these stations has also been complemented by model-based studies. However, assessment of the performance of ionospheric models in capturing observations needs to be conducted. In this work, the performance of the IRI-2016 model in simulating the total electron content (TEC) observed by a network of Global Positioning System (GPS) receivers is evaluated based on the RMSE, the bias, the mean absolute error (MAE) and skill score, the normalized mean bias factor (NMBF), the normalized mean absolute error factor (NMAEF), the correlation, and categorical metrics such as the quantile probability of detection (QPOD), the quantile categorical miss (QCM), and the quantile critical success index (QCSI). The IRI-2016 model simulations are evaluated against gridded International Global Navigation Satellite System (GNSS) Service (IGS) GPS-TEC and TEC observations at a network of GPS receiver stations during the solar minima in 2008 and solar maxima in 2013. The phases of modeled and simulated TEC time series agree strongly over most of the globe, as indicated by a high correlations during all solar activities with the exception of the polar regions. In addition, lower RMSE, MAE, and bias values are observed between the modeled and measured TEC values during the solar minima than during the solar maxima from both sets of observations. The model performance is also found to vary with season, longitude, solar zenith angle, and magnetic local time. These variations in the model skill arise from differences between seasons with respect to solar irradiance, the direction of neutral meridional winds, neutral composition, and the longitudinal dependence of tidally induced wave number four structures. Moreover, the variation in model performance as a function of solar zenith angle and magnetic local time might be linked to the accuracy of the ionospheric parameters used to characterize both the bottom- and topside ionospheres. However, when the NMBF and NMAEF are applied to the data sets from the two distinct solar activity periods, the difference in the skill of the model during the two periods decreases, suggesting that the traditional model evaluation metrics exaggerate the difference in model skill. Moreover, the performance of the model in capturing the highest ends of extreme values over the geomagnetic equator, midlatitudes, and high latitudes is poor, as noted from the decrease in the QPOD and QCSI as well as an increase in the QCM over most of the globe with an increase in the threshold percentile TEC values from 10 % to 90 % during both the solar minimum and the solar maximum periods. The performance of IRI-2016 in simulating observed low (as low as the 10th percentile) and high (higher than the 90th percentile) TEC correctly over equatorial ionization anomaly (EIA) crest regions is reasonably good given that IRI-2016 is a climatological model. However, it is worth noting that the performance of the IRI-2016 model is relatively poor in 2013 compared with 2008 at the highest ends of the TEC distribution. Therefore, this study reveals the strengths and weaknesses of the IRI-2016 model in simulating the observed TEC distribution correctly during all seasons and solar activities for the first time.

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