| Abstract: |
| We study electromagnetic inverse scattering problems at fixed frequency using multi-static data. Classical imaging methods typically fail when the background medium is highly oscillatory. To overcome this limitation, we propose a new method based on the introduction of artificial resonators.
The inverse problem considered here takes as input measurements of scattered waves recorded at large distances from an object, known as the far-field pattern, at a fixed frequency. The goal is to recover information about the internal composition of the probed domain. The general structure of the proposed algorithm is as follows:
\begin{itemize}
\item At a point $z$ in the investigated domain $\Omega$, we numerically introduce an artificial resonator $D_z$.
\item We define in $D_z$ an artificial spectral problem with a unique resonance eigenvalue $\lambda$, and relate this resonance to a quantitative indicator function $I(z)$.
\item The resonance parameter is identified from the far field data using the Inside-Outside Duality method, or the Linear Sampling Method.
\item The indicator function $I(z)$ is computed by sweeping $z$ over the inspected area.
\end{itemize} |
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