loading page

Model-free approach for regional ionospheric multi-instrument imaging
  • +2
  • Johannes Norberg,
  • Sebastian Käki,
  • Lassi Roininen,
  • Jens Mielich,
  • Ilkka I. Virtanen
Johannes Norberg
Finnish meteorological institute

Corresponding Author:jussi.norberg@gmail.com

Author Profile
Sebastian Käki
Finnish Meteorological Institute
Author Profile
Lassi Roininen
Lappeenranta-Lahti University of Technology
Author Profile
Jens Mielich
Leibniz-Institute of Atmospheric Physics (LG)
Author Profile
Ilkka I. Virtanen
University of Oulu
Author Profile


The article proposes a straightforward Kalman filter-based method for computationally efficient ionospheric electron density multi-instrument imaging. The approach uses direct ionospheric measurements, such as ionosondes, and general physical assumptions to estimate the uncertainty associated with the previous reconstructed time step. Therefore the method does not require any electron density model of the ionosphere as a background. The uncertainty is represented by an inverse covariance matrix constructed with Gaussian Markov random fields, allowing the problem to be solved numerically with relatively high resolution. The experiments utilise measurements from dense ground-based GNSS and low Earth orbit beacon satellite receiver networks as well as ionosondes. A synthetic simulation study and real data validation with a specific EISCAT incoherent scatter radar measurement campaign is carried out over Northern European sector. The method can be controlled using parameters with probabilistic and physically realistic interpretations that can be applied to both simulated and real-world data. The results show that the approach is feasible for near real-time regional ionospheric imaging. Especially, the method can be seen as an expansion to local profile measurements field of view, but with sufficient measurement coverage, it also provides information further away from the specific instrument.