Simulation of interferometric imaging with EISCAT_3D for fine-scale in-beam incoherent scatter spectra measurements
Huyghebaert, Devin; Gustavsson, Bjorn; Vierinen, Juha; Kvammen, Andreas; Zettergren, Matthew; Swoboda, John; Virtanen, Ilkka; Hatch, Spencer M.; Laundal, Karl M. (2025-01-24)
Huyghebaert, Devin
Gustavsson, Bjorn
Vierinen, Juha
Kvammen, Andreas
Zettergren, Matthew
Swoboda, John
Virtanen, Ilkka
Hatch, Spencer M.
Laundal, Karl M.
Copernicus publications
24.01.2025
Huyghebaert, D., Gustavsson, B., Vierinen, J., Kvammen, A., Zettergren, M., Swoboda, J., Virtanen, I., Hatch, S. M., & Laundal, K. M. (2025). Simulation of interferometric imaging with EISCAT_3D for fine-scale in-beam incoherent scatter spectra measurements. Annales Geophysicae, 43(1), 99–113. https://doi.org/10.5194/angeo-43-99-2025.
https://creativecommons.org/licenses/by/4.0/
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
https://creativecommons.org/licenses/by/4.0/
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202504172778
https://urn.fi/URN:NBN:fi:oulu-202504172778
Tiivistelmä
Abstract
The 233 MHz EISCAT_3D radar system currently under construction in northern Fennoscandia will be able to resolve ionospheric structures smaller than the transmit beam dimensions through the use of interferometric imaging. This capability is made possible by the modular design and digitization of the 119 panels with 91 antennas each located at the main Skibotn site. The main array consists of a cluster of 109 panels, with 10 outlier panels producing unique interferometry baselines. In the present study, synthesized incoherent scatter radar signal measurements are used for interferometric imaging analysis with the EISCAT_3D system. The Geospace Environment Model of Ion-Neutral Interactions (GEMINI) model is used to simulate a Kelvin–Helmholtz instability in the cusp region at 50 m resolution to obtain plasma parameters which are then used to generate the synthetic data. The ionospheric data are forward-propagated to the EISCAT_3D array, noise is added to the synthetic data, and an inversion of the data is performed to reconstruct the incoherent scatter spectra at relatively fine scales. Using singular value decomposition (SVD) with Tikhonov regularization, it is possible to pre-calculate the inversion matrix for a given range and look direction, with the regularization value scaled based on the signal-to-noise standard deviation ratio (SNSDR). The pre-calculation of the inversion matrix can reduce computational overhead in the imaging solution. This study provides a framework for data processing of ion-line incoherent scatter radar spectra to be imaged at fine scales. Furthermore, with more development, it can be used to test experimental setups and to design experiments for EISCAT_3D by investigating the needed integration time for various SNSDRs, beam patterns, and ionospheric conditions.
The 233 MHz EISCAT_3D radar system currently under construction in northern Fennoscandia will be able to resolve ionospheric structures smaller than the transmit beam dimensions through the use of interferometric imaging. This capability is made possible by the modular design and digitization of the 119 panels with 91 antennas each located at the main Skibotn site. The main array consists of a cluster of 109 panels, with 10 outlier panels producing unique interferometry baselines. In the present study, synthesized incoherent scatter radar signal measurements are used for interferometric imaging analysis with the EISCAT_3D system. The Geospace Environment Model of Ion-Neutral Interactions (GEMINI) model is used to simulate a Kelvin–Helmholtz instability in the cusp region at 50 m resolution to obtain plasma parameters which are then used to generate the synthetic data. The ionospheric data are forward-propagated to the EISCAT_3D array, noise is added to the synthetic data, and an inversion of the data is performed to reconstruct the incoherent scatter spectra at relatively fine scales. Using singular value decomposition (SVD) with Tikhonov regularization, it is possible to pre-calculate the inversion matrix for a given range and look direction, with the regularization value scaled based on the signal-to-noise standard deviation ratio (SNSDR). The pre-calculation of the inversion matrix can reduce computational overhead in the imaging solution. This study provides a framework for data processing of ion-line incoherent scatter radar spectra to be imaged at fine scales. Furthermore, with more development, it can be used to test experimental setups and to design experiments for EISCAT_3D by investigating the needed integration time for various SNSDRs, beam patterns, and ionospheric conditions.
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