Nguyen Trung Thành

2papers

2 Papers

NASep 3, 2014
Globally convergent and adaptive finite element methods in imaging of buried objects from experimental backscattering radar measurements

Larisa Beilina, Nguyen Trung Thành, Michael V. Klibanov et al.

We consider a two-stage numerical procedure for imaging of objects buried in dry sand using time-dependent backscattering experimental radar measurements. These measurements are generated by a single point source of electric pulses and are collected using a microwave scattering facility which was built at the University of North Carolina at Charlotte. Our imaging problem is formulated as the inverse problem of the reconstruction of the spatially distributed dielectric permittivity $\varepsilon_\mathrm{r}\left(\mathbf{x}\right), \ \mathbf{x}\in \mathbb{R}^{3}$, which is an unknown coefficient in Maxwell's equations. On the first stage an approximately globally convergent method is applied to get a good first approximation for the exact solution. On the second stage a local adaptive finite element method is applied to refine the solution obtained on the first stage. The two-stage numerical procedure results in accurate imaging of all three components of interest of targets: shapes, locations and refractive indices. In this paper we briefly describe methods and present new reconstruction results for both stages.

NAMar 4, 2015
Numerical studies of an adaptive finite element method applied to the reconstruction of shapes of buried objects from experimental data

Larisa Beilina, Nguyen Trung Thành, Michael V. Klibanov et al.

We perform extended studies of an adaptive finite element method applied to the reconstruction of shapes of buried objects from experimental backscattering data. We use experimental data which are collected by a microwave scattering facility located at the University of North Carolina at Charlotte, USA. Our numerical tests show accurate imaging of three components of interest of targets: shapes, locations and refractive indices.