A New Approach for 4-D Exospheric Tomography Based on Optimal Interpolation and Gaussian Markov Random Fields

Gonzalo Cucho-Padin, Humberto Godinez, Lara Waldrop, Igor Baliukin, Dolon Bhattacharyya, David Sibeck, Michael Henderson

Research output: Contribution to journalArticlepeer-review

Abstract

Exospheric tomography is a computational 3-D imaging technique that provides the estimates of the neutral density distributions of the terrestrial exosphere from space-based ultraviolet (UV) measurements. Variability of neutral densities during geomagnetically active conditions has been previously reported, motivating the development of time-dependent tomographic techniques that can characterize both the spatial and temporal scales of densities during these events. However, solving the dynamic exospheric tomography problem can be challenging owing to its ill-posedness. In this letter, we introduce a novel algorithm for 4-D exospheric tomography based on optimal interpolation (OI) and Gaussian Markov random field (GMRF) theory. The OI analysis enables iterative reconstructions of the exosphere when a statistical background field is provided. Its mean is selected from previous knowledge of the exosphere, and its covariance matrix is estimated using GMRF. To validate the performance, we apply our proposed methodology to six days of UV data acquired by National Aeronautics and Space Administration (NASA) two-wide angle imaging neutral-atom spectrometer (TWINS) mission during the geomagnetic storm that occurred on June 15, 2008.

Original languageEnglish (US)
Article number1000505
JournalIEEE Geoscience and Remote Sensing Letters
Volume20
DOIs
StatePublished - 2023
Externally publishedYes

Keywords

  • Bayesian theory
  • Correlation
  • Covariance matrices
  • Earth
  • Exospheric tomography
  • Interpolation
  • Markov random fields
  • Photonics
  • Tomography
  • inverse problems
  • optical remote sensing
  • exospheric tomography

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering

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