Efficiency of updating the ionospheric models using total electron content at mid- and sub-auroral latitudes

Kotova, Daria; Ovodenko, Vladimir B.; Yasyukevich, Yury; Клименко, М. В.; Ratovsky, Konstantin; Mylnikova, Anna; Andreeva, Elena; Kozlovsky, Alexander; Korenkova, N.A.; Nesterov, Ivan; Tumanova, Yulia

doi:10.1007/s10291-019-0936-x

Cited by 11 publications

(4 citation statements)

References 41 publications

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“…2021, 13, 3973 2 of 14 GNSS TEC provides a basis for different techniques: GNSS radio tomography [9][10][11], GNSS radio interferometry of travelling ionospheric disturbances (TID) [12], ionosphere mapping [13,14], absolute TEC estimation [15], and ionospheric perturbation indices estimation [16][17][18]. Scientists use these techniques and data to study space weather, to create empirical or first principal ionospheric models [19,20], to estimate the quality of different models [21,22], and to update ionospheric models [23].…”

Section: Introductionmentioning

confidence: 99%

Galileo E5 AltBOC Signals: Application for Single-Frequency Total Electron Content Estimations

et al. 2021

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Global navigation satellite system signals are known to be an efficient tool to monitor the Earth ionosphere. We suggest Galileo E5 AltBOC phase and pseudorange observables— a single-frequency combination—to estimate the ionospheric total electron content (TEC). We performed a one-month campaign in September 2020 to compare the noise level for different TEC estimations based on single-frequency and dual-frequency data. Unlike GPS, GLONASS, or Galileo E5a and E5b single-frequency TEC estimations (involving signals with binary and quadrature phase-shift keying, such as BPSK and QPSK, or binary offset carrier (BOC) modulation), an extra wideband Galileo E5 AltBOC signal provided the smallest noise level, comparable to that of dual-frequency GPS. For elevation higher than 60 degrees, the 100-sec root-mean-square (RMS) of TEC, an estimated TEC noise proxy, was as follows for different signals: ~0.05 TECU for Galileo E5 AltBOC, 0.09 TECU for GPS L5, ~0.1TECU for Galileo E5a/E5b BPSK, and 0.85 TECU for Galileo E1 CBOC. Dual-frequency phase combinations provided RMS values of 0.03 TECU for Galileo E1/E5, 0.03 and 0.07 TECU for GPS L1/L2 and L1/L5. At low elevations, E5 AltBOC provided at least twice less single-frequency TEC noise as compared with data obtained from E5a or E5b. The short dataset of our study could limit the obtained estimates; however, we expect that the AltBOC single-frequency TEC will still surpass the BPSK analogue in noise parameters when the solar cycle evolves and geomagnetic activity increases. Therefore, AltBOC signals could advance geoscience.

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Section: Introductionmentioning

confidence: 99%

Galileo E5 AltBOC Signals: Application for Single-Frequency Total Electron Content Estimations

et al. 2021

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“…Visual inspection of the 2D anomaly maps of N m F2 versus VTEC (as in Figure 4) may suggest that observed delta-VTEC features may be simply duplicated and then suitably superimposed and blended with the N m F2 map, thus accomplishing its better resolution and additional coverage of missing data. Statistically, variation of VTEC was indeed reported, often matching that of N m F2 (e.g., [56] and references therein). However, up to 50% of the VTEC must be attributed to the plasmasphere content above the ionosphere [57], which introduces significant and, in many cases, unacceptable uncertainty regarding whether such direct attribution of delta-VTEC to delta-N m F2 is realistic.…”

Section: Fusing Giro and Gnss Datamentioning

confidence: 67%

Global Monitoring of Ionospheric Weather by GIRO and GNSS Data Fusion

et al. 2022

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Prompt and accurate imaging of the ionosphere is essential to space weather services, given a broad spectrum of applications that rely on ionospherically propagating radio signals. As the 3D spatial extent of the ionosphere is vast and covered only fragmentarily, data fusion is a strong candidate for solving imaging tasks. Data fusion has been used to blend models and observations for the integrated and consistent views of geosystems. In space weather scenarios, low latency of the sensor data availability is one of the strongest requirements that limits the selection of potential datasets for fusion. Since remote plasma sensing instrumentation for ionospheric weather is complex, scarce, and prone to unavoidable data noise, conventional 3D-var assimilative schemas are not optimal. We describe a novel substantially 4D data fusion service based on near-real-time data feeds from Global Ionosphere Radio Observatory (GIRO) and Global Navigation Satellite System (GNSS) called GAMBIT (Global Assimilative Model of the Bottomside Ionosphere with Topside estimate). GAMBIT operates with a few-minute latency, and it releases, among other data products, the anomaly maps of the effective slab thickness (EST) obtained by fusing GIRO and GNSS data. The anomaly EST mapping aids understanding of the vertical plasma restructuring during disturbed conditions.

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“…The developed software may be used to calculate the vertical TEC from the local networks or to locally update ionosphere models [ 61 ]. The vertical TEC obtained through this procedure generally agrees with the TEC from the IONOLAB and CODE GIM.…”

Section: Discussionmentioning

confidence: 99%

GNSS-Based Non-Negative Absolute Ionosphere Total Electron Content, its Spatial Gradients, Time Derivatives and Differential Code Biases: Bounded-Variable Least-Squares and Taylor Series

Yasyukevich

Mylnikova

Vesnin

2020

Sensors

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Global navigation satellite systems (GNSS) allow estimating total electron content (TEC). However, it is still a problem to calculate absolute ionosphere parameters from GNSS data: negative TEC values could appear, and most of existing algorithms does not enable to estimate TEC spatial gradients and TEC time derivatives. We developed an algorithm to recover the absolute non-negative vertical and slant TEC, its derivatives and its gradients, as well as the GNSS equipment differential code biases (DCBs) by using the Taylor series expansion and bounded-variable least-squares. We termed this algorithm TuRBOTEC. Bounded-variable least-squares fitting ensures non-negative values of both slant TEC and vertical TEC. The second order Taylor series expansion could provide a relevant TEC spatial gradients and TEC time derivatives. The technique validation was performed by using independent experimental data over 2014 and the IRI-2012 and IRI-plas models. As a TEC source we used Madrigal maps, CODE (the Center for Orbit Determination in Europe) global ionosphere maps (GIM), the IONOLAB software, and the SEEMALA-TEC software developed by Dr. Seemala. For the Asian mid-latitudes TuRBOTEC results agree with the GIM and IONOLAB data (root-mean-square was < 3 TECU), but they disagree with the SEEMALA-TEC and Madrigal data (root-mean-square was >10 TECU). About 9% of vertical TECs from the TuRBOTEC estimates exceed (by more than 1 TECU) those from the same algorithm but without constraints. The analysis of TEC spatial gradients showed that as far as 10–15° on latitude, TEC estimation error exceeds 10 TECU. Longitudinal gradients produce smaller error for the same distance. Experimental GLObal Navigation Satellite System (GLONASS) DCB from TuRBOTEC and CODE peaked 15 TECU difference, while GPS DCB agrees. Slant TEC series indicate that the TuRBOTEC data for GLONASS are physically more plausible.

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Efficiency of updating the ionospheric models using total electron content at mid- and sub-auroral latitudes

Cited by 11 publications

References 41 publications

Galileo E5 AltBOC Signals: Application for Single-Frequency Total Electron Content Estimations

Galileo E5 AltBOC Signals: Application for Single-Frequency Total Electron Content Estimations

Global Monitoring of Ionospheric Weather by GIRO and GNSS Data Fusion

GNSS-Based Non-Negative Absolute Ionosphere Total Electron Content, its Spatial Gradients, Time Derivatives and Differential Code Biases: Bounded-Variable Least-Squares and Taylor Series

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