Remote Sensing (Jun 2023)

Real-Time Tomographic Inversion of Truncated Ionospheric GNSS Radio Occultations

  • Germán Olivares-Pulido,
  • Manuel Hernández-Pajares,
  • Enric Monte-Moreno,
  • Haixia Lyu,
  • Victoria Graffigna,
  • Estel Cardellach,
  • Mainul Hoque,
  • Fabricio S. Prol,
  • Riccardo Notarpietro,
  • Miquel Garcia-Fernandez

DOI
https://doi.org/10.3390/rs15123176
Journal volume & issue
Vol. 15, no. 12
p. 3176

Abstract

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This paper presents a new way of combining Abel inversion and the Chapman model with a linearly increasing scale height to retrieve ionospheric electron density vertical profiles from truncated-sounding radio-occultation data. A linear Vary–Chap model is used to cover the blind region due to data truncation, with parameters estimated by enumeration of the possible values in a grid centered around a set of parameters compatible with ionospheric physics. The resulting electron density is estimated with its corresponding error from the linear least-squares solution presenting the smaller post-fit residual on the input GNSS carrier-phase measurements. The results, tested on a set of representative GNSS RO measurements obtained by COSMIC/FORMOSAT-3, show that this method can retrieve EDVPs with a predominant absolute and relative error of 1010e−m−3 and 5%, respectively, and in less than 10 s per profile, which makes this method suitable for near real-time applications in upcoming missions such as EUMETSAT Polar System-Second Generation.

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