Articles | Volume 9, issue 4
https://doi.org/10.5194/amt-9-1859-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-1859-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| Highlight paper
| 
28 Apr 2016
Research article | Highlight paper |
| 28 Apr 2016
Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements
Johannes Norberg
CORRESPONDING AUTHOR
Finnish Meteorological Institute, Helsinki, Finland
Sodankylä Geophysical Observatory, University of Oulu, Sodankylä, Finland
Ilkka I. Virtanen
Ionospheric Physics, University of Oulu, Oulu, Finland
Lassi Roininen
Sodankylä Geophysical Observatory, University of Oulu, Sodankylä, Finland
Department of Mathematics, Tallinn University of Technology, Tallinn, Estonia
Juha Vierinen
Haystack Observatory, Massachusetts Institute of Technology, Westford, MA, USA
Mikko Orispää
Sodankylä Geophysical Observatory, University of Oulu, Sodankylä, Finland
Department of Mathematics, Tallinn University of Technology, Tallinn, Estonia
Kirsti Kauristie
Finnish Meteorological Institute, Helsinki, Finland
Markku S. Lehtinen
Sodankylä Geophysical Observatory, University of Oulu, Sodankylä, Finland
Department of Mathematics, Tallinn University of Technology, Tallinn, Estonia
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Cited
12 citations as recorded by crossref.
- 3-D Ionospheric Tomography Using Model Function in the Modified L-Curve Method S. Wang et al.
- OTHR multitarget tracking with a GMRF model of ionospheric parameters Z. Guo et al.
- Two-dimensional ionospheric radio-tomography by nanosatellite constellation receiving signals from the GLONASS navigation system I. Belokonov et al.
- Ionospheric reconstruction from LEO-GNSS, LEO-PNT, and ground-GNSS using an information-filter L. Schreiter et al.
- Rapid filtered back-projection algorithm in 2D ionospheric radio tomography using satellite-to-satellite measurements P. Nikolaev et al.
- Model‐Free Approach for Regional Ionospheric Multi‐Instrument Imaging J. Norberg et al.
- Dual Empirical Orthogonal Functions Restrained Tomographic Model for Ionosphere Imaging J. Yu et al.
- Ionospheric tomography by gradient-enhanced kriging with STEC measurements and ionosonde characteristics D. Minkwitz et al.
- Three‐dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization S. Wang et al.
- An Extended Simultaneous Algebraic Reconstruction Technique for Imaging the Ionosphere Using GNSS Data and Its Preliminary Results Y. Long et al.
- Gaussian Markov Random Field Priors in Ionospheric 3-D Multi-Instrument Tomography J. Norberg et al.
- An improved method using adaptive smoothing for GNSS tomographic imaging of ionosphere R. Jia et al.
12 citations as recorded by crossref.
- 3-D Ionospheric Tomography Using Model Function in the Modified L-Curve Method S. Wang et al.
- OTHR multitarget tracking with a GMRF model of ionospheric parameters Z. Guo et al.
- Two-dimensional ionospheric radio-tomography by nanosatellite constellation receiving signals from the GLONASS navigation system I. Belokonov et al.
- Ionospheric reconstruction from LEO-GNSS, LEO-PNT, and ground-GNSS using an information-filter L. Schreiter et al.
- Rapid filtered back-projection algorithm in 2D ionospheric radio tomography using satellite-to-satellite measurements P. Nikolaev et al.
- Model‐Free Approach for Regional Ionospheric Multi‐Instrument Imaging J. Norberg et al.
- Dual Empirical Orthogonal Functions Restrained Tomographic Model for Ionosphere Imaging J. Yu et al.
- Ionospheric tomography by gradient-enhanced kriging with STEC measurements and ionosonde characteristics D. Minkwitz et al.
- Three‐dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization S. Wang et al.
- An Extended Simultaneous Algebraic Reconstruction Technique for Imaging the Ionosphere Using GNSS Data and Its Preliminary Results Y. Long et al.
- Gaussian Markov Random Field Priors in Ionospheric 3-D Multi-Instrument Tomography J. Norberg et al.
- An improved method using adaptive smoothing for GNSS tomographic imaging of ionosphere R. Jia et al.
Saved (final revised paper)
Latest update: 05 May 2026
Short summary
We validate 2-D ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. The method is based on Bayesian statistical inversion. We employ ionosonde measurements for the choice of the prior distribution parameters and use a sparse matrix approximation for the computations. This results in a computationally efficient tomography algorithm with clear probabilistic interpretation. We find that ionosonde measurements improve the reconstruction significantly.
We validate 2-D ionospheric tomography reconstructions against EISCAT incoherent scatter radar...
