Bibliography

Application of BDS-GEO for studying TEC variability in equatorial ionosphere on different time scales

The GUVI data are provided through support from the NASA MO&DA program. The GUVI instrument was designed and built by The Aerospace Corporation and The Johns Hopkins

Padokhin, AM; Tereshin, NA; Yasyukevich, Yu; Andreeva, ES; Nazarenko, MO; Yasyukevich, AS; Kozlovtseva, EA; Kurbatov, GA;

Published by: Advances in Space Research      Published on:

YEAR: 2019     DOI: 10.1016/j.asr.2018.08.001

Modeling the problem of low-orbital satellite UV-tomography of the ionosphere

The results of modeling the direct and inverse problems of low-orbital satellite ultraviolet (UV) tomography of the ionospheric 135.6 OI volume emission rate are presented. The direct problem was solved with the orbital geometry of DMSP block 5D3 satellites with SSUSI and SSULI UV spectrographs among the other payloads, the real operating parameters of these instruments (the scan rate and the interval of scan angles), and the set of the model distributions of the volume emission rate that contain irregularities on various scales. The solution of the direct problem yields the radiation intensities in the 135.6 nm line, which is used as the input data for reconstructing the initial (prototype) model distributions of the volume emission rates. The obtained system of linear equations (SLE) was solved using the Algebraic Reconstruction Technique (ART) and Simultaneous Iterative Reconstructive Technique (SIRT) algorithms, which are highly efficient in problems of the low-orbit radio tomography of the ionosphere. It is shown that the initial model distribution can be successively reconstructed if one takes the non-negativity condition of the solution into account, uses weighting functions to decrease the solution in the regions where it is known to be a priori small, and applies inter-iteration smoothing to eliminate the effects of the approximation errors. Here, the averaging parameters should decrease in the course of the iterations. With these constraints fulfilled, the computational costs of the ART- and SIRT-based solutions are similar, while the reconstruction error is approximately 6\%. The influence of random errors and bias in the data on the results of the reconstruction is explored. It is shown that with a given error level of the initial data the parameters of the reconstruction algorithms can be adjusted in such a way as to efficiently suppress the influence of the noise with a relative amplitude of 2\textendash3\% on the solution.

Nesterov, I.; Padokhin, A.; Andreeva, E.; Kalashnikova, S.;

Published by: Moscow University Physics Bulletin      Published on: 06/2016

YEAR: 2016     DOI: 10.3103/S0027134916030103

Earthquake prediction research using radio tomography of the ionosphere

Under development since its invention in 1990 as an ancillary application of ionospheric radio-tomography (RT), a new earthquake (EQ) prediction system is being evaluated. It has already been deployed along the United States West Coast, from Vancouver in Canada to San Diego in Southern California, and is currently undergoing Beta testing. This Chapter addresses RT\textendashEQ prediction concepts, the underlying RT theory, evolution and implementation, and a few examples of the Beta test system\textquoterights performance. This work is an investigation of EQ precursors, which we hope will lead to an operational system. The current system provides a foundation and the tools to study ionospheric effects linked to conditions in the Earth\textquoterights crust prior to major earthquakes. Progress toward a fully operational system will require several more years of data acquisition and analysis.

Kunitsyn, Vyacheslav; Andreeva, Elena; Nesterov, Ivan; Padokhin, Artem; Gribkov, Dmitrii; Rekenthaler, Douglas;

Published by:       Published on:

YEAR: 2014     DOI: 10.1007/978-3-319-02207-9_15

Total electron content mapping using global navigation satellite systems

Kunitsyn, VE; Andreeva, ES; Nesterov, IA; Kalashnikova, SA; Padokhin, AM;

Published by:       Published on:

YEAR: 2012     DOI:

TEC studies by satellite navigation.

Kunitsyn, VE; Andreeva, ES; Nesterov, IA; Kalashnikova, SA; Padokhin, AM;

Published by:       Published on:

YEAR: 2011     DOI:

Comparison of global ionospheric maps, high-orbital and low-orbital radio tomography.

Observations on the GPS receivers networks which are being actively developed at present provide the input data for constructing global ionospheric maps (GIM) of the distributions of total electron content (TEC) in the ionosphere. The methods applied in the GIM construction at several data processing centers are different although all based on the common idea of finding the appropriate model parameters to fit the selected model of the vertical distribution of electron density to the observed GPS data. At the same time, the existing global IGS network together with several regional GPS networks open the possibility for solving the problem of 4D (spatiotemporal) ionospheric radio tomography (RT) based on the data of high-orbiting navigational satellite systems (the high orbital radio tomography, HORT). The approaches used in HORT are similar to those applied and found highly efficient in 2D low-orbital radio tomography (LORT). The purpose of the present work is to compare TEC estimations based on GIMs, calculated by different centers, with HORT and LORT reconstructions observed at different geomagnetic activity. The results of such comparison along RT systems in Russia and Alaska during the periods of geomagnetic storms of 2003-2004 are reported and discussed. The reconstructions for quiet periods are basically similar, although higher GIM and HORT TEC compared to LORT TEC, which might be due to the plasmaspheric contribution, are still noteworthy. However, during the geomagnetic storms, GIM TEC significantly differs from either LORT and HORT TEC. The work was supported by the Russian Foundation for Basic Research (grants nos. 10-05-01126, 08-05-00676). The authors acknowledge IGS for GNSS data. We are also grateful to our colleagues in PGI and NWRS for the shared raw RT data.

Kunitsyn, V.~E.; Andreeva, E.~S.; Nesterov, I.~A.; Kalashnikova, S.~A.; Padokhin, A.~M.;

Published by:       Published on:

YEAR: 2010     DOI: