Simulation of interferometric imaging with EISCAT_3D for fine-scale in-beam incoherent scatter spectra measurements
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| Gepubliceerd in: | Annales Geophysicae vol. 43, no. 1 (2025), p. 99 |
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| Andere auteurs: | , , , , , , , |
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| 024 | 7 | |a 10.5194/angeo-43-99-2025 |2 doi | |
| 035 | |a 3158997158 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
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| 100 | 1 | |a Huyghebaert, Devin |u Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway; Department of Physics and Engineering Physics, University of Saskatchewan, Saskatoon, Canada | |
| 245 | 1 | |a Simulation of interferometric imaging with EISCAT_3D for fine-scale in-beam incoherent scatter spectra measurements | |
| 260 | |b Copernicus GmbH |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 651 | 4 | |a Norway | |
| 653 | |a Receivers & amplifiers | ||
| 653 | |a Outliers (statistics) | ||
| 653 | |a Signal processing | ||
| 653 | |a Kelvin-Helmholtz instability | ||
| 653 | |a Interferometry | ||
| 653 | |a Noise standards | ||
| 653 | |a Data analysis | ||
| 653 | |a Regularization | ||
| 653 | |a Fourier transforms | ||
| 653 | |a Modular design | ||
| 653 | |a Environment models | ||
| 653 | |a Antenna arrays | ||
| 653 | |a Plasma | ||
| 653 | |a Scatter propagation | ||
| 653 | |a Data processing | ||
| 653 | |a Spectra | ||
| 653 | |a Noise reduction | ||
| 653 | |a Chemical synthesis | ||
| 653 | |a Antennas | ||
| 653 | |a Incoherent scatter radar | ||
| 653 | |a Ionosphere | ||
| 653 | |a Radar imaging | ||
| 653 | |a Radar | ||
| 653 | |a Singular value decomposition | ||
| 653 | |a Signal to noise ratio | ||
| 653 | |a Scattering | ||
| 653 | |a Ionospheric conditions | ||
| 653 | |a Modular systems | ||
| 653 | |a Noise propagation | ||
| 653 | |a Panels | ||
| 653 | |a Radar equipment | ||
| 653 | |a Modular structures | ||
| 653 | |a Radar systems | ||
| 653 | |a Line spectra | ||
| 653 | |a Synthetic data | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Gustavsson, Björn |u Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway | |
| 700 | 1 | |a Vierinen, Juha |u Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway | |
| 700 | 1 | |a Kvammen, Andreas |u Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway | |
| 700 | 1 | |a Zettergren, Matthew |u Embry–Riddle Aeronautical University, Daytona Beach, FL, USA | |
| 700 | 1 | |a Swoboda, John |u MIT Haystack Observatory, Westford, MA, USA | |
| 700 | 1 | |a Virtanen, Ilkka |u Space Physics and Astronomy Research Unit, University of Oulu, Oulu, Finland | |
| 700 | 1 | |a Hatch, Spencer M |u Department of Physics and Technology, University of Bergen, Bergen, Norway | |
| 700 | 1 | |a Laundal, Karl M |u Department of Physics and Technology, University of Bergen, Bergen, Norway | |
| 773 | 0 | |t Annales Geophysicae |g vol. 43, no. 1 (2025), p. 99 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3158997158/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3158997158/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3158997158/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |