No abstract

We investigate two imaging methods to detect buried scatterers from electromagnetic measurements at a fixed frequency. The first one is the classical linear sampling method that requires the computation of Green's tensor for the background medium. This job can be numerically very costly for complex background geometries. The second one is an alternative approach based on the reciprocity gap functional that avoids the computation of Green's tensor but requires knowledge of both the electric and magnetic fields. Numerical examples are given showing the performance of both methods.

mA general ab initio package using Slater- proach potentially offers the best prospects in view of its limitations which are purely related to calculation times currently improving with the advent of more powerful computers. Ab initio calculations using the LCAO-MO [l] strategy are strongly dependent on the choice of basis functions [2, 31 for the reliability of the elec-

We present in this study some three-dimensional numerical results that validate the use of the linear sampling method as an inverse solver in electromagnetic scattering problems. We recall that this method allows the reconstruction of the shape of an obstacle from the knowledge of multi-static radar data at a fixed frequency. It does not require any a priori knowledge of the physical properties of the scatterer nor any nonlinear optimization scheme. This study also contains some analytical results in the simplified case of a spherical scatterer that somehow make the link between known abstract theoretical results and the numerical scheme. Special attention has been given to pointing out the influence of the frequency on the inversion accuracy.

No abstract