Buried object detection by means of a Lp Banach-space inversion procedure

Electromagnetic inspection techniques are becoming powerful tools for buried object detection and subsurface prospection in several applicative fields, such as civil engineering and archeology. However, the nonlinearity and ill-posedness of the underlying inverse problem make the development of efficient imaging techniques a very challenging task. In the present paper, an algorithm based on a regularizing approach in L
^p
Banach spaces is proposed for tackling such problems. The effectiveness of the approach is verified by means of numerical simulations in a noisy environment aimed at evaluating the reconstruction capabilities with respect to the choice of several model parameters. The reported results show that, for small targets, the use of L
^p
Banach spaces with 1 < p < 2 allows to obtain a better localization of different buried scatterers.