Microwave imaging exploits the interaction of an electromagnetic wave with its surrounding environment. Once the scattered field is measured, a dedicated inversion scheme is implemented in order to extract from the dataset the electromagnetic and geometrical features of the target under illumination.
We are more particularly focussed on the algorithmic development associated to these inverse problems with methods such as:
Non-iterative qualitative techniques (backpropagation, scattering tomography [1], DORT [2] , Linear Sampling Method, MUSIC , fields correlations [3], …)
Iterative quantitative techniques (Newton methods, adjoint states [4] [5]) with the incorporation of a priori information :
level-set algorithm for homogeneous-by-part targets [6],
Decomposition onto orthogonal basis sets [7,8],
Regularisation,
Bayesian approach with a measurement noise model [9, 10].
Thanks to these inverse problems algorithms, it is possible to image targets in various types of environments, such as free-space [12], [4], stratified media [3], [11], cavities [2], [7,8].
Contact : Amélie Litman
Mots-clés : Problèmes inverses, imagerie par diffraction, imagerie quantitative, contrôle non-destructif, imagerie à partir de mesures
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