A high-resolution imaging of objects embedded in a lossy dispersive medium

Most of techniques used in subsurface radar applications, such as the aperture synthesis or the pulse compression, are developed originally for conventional radars which use the air as the propagation medium. Among the features that specialize subsurface radar, the loss and dispersion of the medium together with the existence of strong clutters strictly limit the usefulness of these techniques. For an accurate imaging of subsurface objects, it is thus essential to develop an algorithm which can handle these features. While it is very hard to include the effect of loss and dispersion in inverse scattering problems, various numerical procedures have already been developed for the forward scattering case. The authors' approach has been to model the target with a limited number of parameters, and to recursively modify them so that the observed signal waveforms fit the estimated ones computed for the model. Their previous algorithm (1996) is, however, applicable only to the case of lossless and non-dispersive medium. In this paper, they extend it to handle a more realistic case of target imaging in a two-dimensional homogeneous lossy and dispersive medium.