An innovative inverse scattering (IS) methodology is presented for imaging targets within inhomogeneous media. It consists of a joint inversion scheme enabling the simultaneous processing of electromagnetic (EM) and acoustic (AC) data while iteratively zooming on the detected region-of-interest (RoI) in which the scatterer has been detected. Robust and reliable guesses are yielded thanks to the combination of multiphysics data, providing complementary information on the imaged domain, with the available a-priori knowledge of the reference inhomogeneous distribution. Furthermore, the integration within a multiscale procedure allows one to keep the ratio between unknowns and data as low as possible, thus counteracting the non-linearity while further regularizing the inversion thanks to the introduction of progressively-acquired information. A preliminary numerical benchmark is shown to assess the capabilities of the proposed multiscale-multiphysics methodology. © 2024 18th European Conference on Antennas and Propagation, EuCAP 2024. All Rights Reserved.
Recent Advances in Multiscale-Multiphysics Inverse Scattering / Salucci, M., Poli, L., Lusa, S., Lin, Z., Li, M., Massa, A.. - STAMPA. - (2024), pp. 1-4. (18th European Conference on Antennas and Propagation, EuCAP 2024 Glasgow, United Kingdom 17th March -22th March 2024) [10.23919/eucap60739.2024.10501373].
Recent Advances in Multiscale-Multiphysics Inverse Scattering
Salucci, Marco;Poli, Lorenzo;Lusa, Samantha;Massa, Andrea
2024-01-01
Abstract
An innovative inverse scattering (IS) methodology is presented for imaging targets within inhomogeneous media. It consists of a joint inversion scheme enabling the simultaneous processing of electromagnetic (EM) and acoustic (AC) data while iteratively zooming on the detected region-of-interest (RoI) in which the scatterer has been detected. Robust and reliable guesses are yielded thanks to the combination of multiphysics data, providing complementary information on the imaged domain, with the available a-priori knowledge of the reference inhomogeneous distribution. Furthermore, the integration within a multiscale procedure allows one to keep the ratio between unknowns and data as low as possible, thus counteracting the non-linearity while further regularizing the inversion thanks to the introduction of progressively-acquired information. A preliminary numerical benchmark is shown to assess the capabilities of the proposed multiscale-multiphysics methodology. © 2024 18th European Conference on Antennas and Propagation, EuCAP 2024. All Rights Reserved.| File | Dimensione | Formato | |
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