Vestnik КRAUNC. Fiz.-Mat. nauki. 2023. vol. 45. no. 4. P. 95-108. ISSN 2079-6641

Research Article
Full text in Russian
MSC 86A25

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Reconstruction of Regional Distributions of Electron Density in the Ionosphere from Heterogeneous Remote Sensing Data

I. A. Pavlov^\ast, A. M. Padokhin

Department of Physics of Atmosphere, Faculty of Physics, Lomonosov Moscow State University, Moscow 119991, Russia.

Abstract. A new iterative algorithm has been developed for solving the problem of reconstructing regional distributions of electron density in the ionosphere based on heterogeneous data from low-orbit satellite radio sounding at a pair of coherent frequencies VHF/UHF and UV spectrometry of the upper atmosphere’s airglow at 135.6 nm. It allows us to use complementary probing geometries. Each iteration of the algorithm is split into two, in which problems concerning the electron concentration and its square are sequentially solved with diffusion smoothing between steps. In addition, the algorithm implements the possibility of taking into account the absorption of the intrinsic UV radiation of the thermosphere by molecular oxygen, which makes it possible to include low perigee rays, the absorption of which plays a significant role, into consideration. The developed algorithm was tested on synthetic observational data obtained on the basis of the NRLMSISE00 and NeQuick2 models for real operation modes of the CERTO and SSUSI/SSULI equipment. It is shown that the proposed algorithm provides better spatial resolution compared to the traditional RT approach, and also removes the problem of correctly specifying the initial approximation, due to the presence of quasi-horizontal rays in the sounding geometry.

Key words: ionosphere, tomography, modelling.

Received: 01.11.2023; Revised: 10.12.2023; Accepted: 12.12.2023; First online: 15.12.2023

For citation. Pavlov I. A., Padokhin A. M. Reconstruction of regional distributions of electron density in the
ionosphere from heterogeneous remote sensing data.. Vestnik KRAUNC. Fiz.-mat. nauki. 2023, 45: 4, 95-108. EDN: PJWWSZ.

Funding. The work is supported by RSF, project 22-27-00396

Competing interests. There are no conflicts of interest regarding authorship and publication.

Contribution and Responsibility. All authors contributed to this article. Authors are solely responsible for providing the final version of the article in print. The final version of the manuscript was approved by all authors.

[kaex]^\ast[/katex]Correspondence: E-mail:

The content is published under the terms of the Creative Commons Attribution 4.0 International License

© Pavlov I. A., Padokhin A. M., 2023

© Institute of Cosmophysical Research and Radio Wave Propagation, 2023 (original layout, design, compilation)


  1. Kunitsyn V. E., Tereshchenko E. D., Andreeva E. S. Radiotomography of the Ionosphere (In Russian).
  2. Dymond K. F., Budzien S. A., Hei M. A. Ionospheric-thermospheric UV tomography: 1. Image space reconstruction algorithms. Radio Science. 2017. vol. 52. no. 3. pp. 338-356.
  3. Hei M. A. et al. Ionospheric-thermospheric UV tomography: 3. A multisensor technique for creating full-orbit reconstructions of atmospheric UV emission. Radio Science. 2017. vol. 52. no. 7. pp. 896-916.
  4. Nesterov I. A. et al. Modeling the problem of low-orbital satellite UV-tomography of the ionosphere. Moscow University Physics Bulletin. 2016. vol. 71. pp. 329-338.
  5. Picone J. M. et al. NRLMSISE-00 empirical model of the atmosphere: Statistical comparisons and scientific issues. Journal of Geophysical Research: Space Physics. 2002. vol. 107. no. A12. SIA 15-1-SIA 15-16.
  6. Nava B., Coisson P., Radicella S. M. A new version of the NeQuick ionosphere electron density model. Journal of atmospheric and solar-terrestrial physics. 2008. vol. 70. no. 15. pp. 1856-1862.
  7. Bernhardt P. A., Siefring C. L. New satellite-based systems for ionospheric tomography and scintillation region imaging. Radio science. 2006. vol. 41. no. 5. pp. 1-14.
  8. Dymond K. F. et al. The special sensor ultraviolet limb imager instruments. Journal of Geophysical Research: Space Physics. 2017. vol. 122. no. 2. pp. 2674-2685.
  9. Tinsley B. A., Bittencourt J. A. Determination of F region height and peak electron density at night using airglow emissions from atomic oxygen. Journal of Geophysical Research. 1975. vol. 80. no. 16. pp. 2333-2337.
  10. Dymond K. F. et al. An optical remote sensing technique for determining nighttime F region electron density. Radio Science. 1997. vol. 32. no. 5. pp. 1985-1996.
  11. Qin J. et al. Radiative transfer modeling of the OI 135.6 nm emission in the nighttime ionosphere. Journal of Geophysical Research: Space Physics. 2015. vol. 120. no. 11. p. 10116-10135.
  12. Richard Gordon, Robert Bender, Gabor T. Herman, Algebraic Reconstruction Techniques (ART) for three-dimensional electron microscopy and X-ray photography, Journal of Theoretical Biology, 1970. p. 471-481

Information about authors

Pavlov Ilia Aleksandrovich – Postgraduate student, Department of Atmospheric Physics, Faculty of Physics, Moscow State University, Moscow, Russia, ORCID 0009-0002-3330-8880.

Padokhin Artem Mikhailovich – PhD. (Phys. & Math.), Associate Professor, Department of Atmospheric Physics, Faculty of Physics, Moscow State University, Moscow, Russia, ORCID 0000-0002-0190-2140.