On orthogonality sampling method for Maxwell's equations and its applications to experimental data
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866912212467056640 |
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| author | Le, Thu Nguyen, Dinh-Liem |
| author_facet | Le, Thu Nguyen, Dinh-Liem |
| contents | This paper addresses the inverse scattering problem for Maxwell's equations. We first show that a bianisotropic scatterer can be uniquely determined from multi-static far-field data through the factorization analysis of the far-field operator. Next, we investigate a modified version of the orthogonality sampling method, as proposed in Le [2022 Inverse Problems 38 025007], for the numerical reconstruction of the scatterer. Finally, we apply this sampling method to invert unprocessed 3D experimental data obtained from the Fresnel Institute. Numerical examples with synthetic scattering data for bianisotropic targets are also presented to demonstrate the effectiveness of the method. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2412_11825 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On orthogonality sampling method for Maxwell's equations and its applications to experimental data Le, Thu Nguyen, Dinh-Liem Numerical Analysis 35R30, 78A46 This paper addresses the inverse scattering problem for Maxwell's equations. We first show that a bianisotropic scatterer can be uniquely determined from multi-static far-field data through the factorization analysis of the far-field operator. Next, we investigate a modified version of the orthogonality sampling method, as proposed in Le [2022 Inverse Problems 38 025007], for the numerical reconstruction of the scatterer. Finally, we apply this sampling method to invert unprocessed 3D experimental data obtained from the Fresnel Institute. Numerical examples with synthetic scattering data for bianisotropic targets are also presented to demonstrate the effectiveness of the method. |
| title | On orthogonality sampling method for Maxwell's equations and its applications to experimental data |
| topic | Numerical Analysis 35R30, 78A46 |
| url | https://arxiv.org/abs/2412.11825 |