Analyses of Autofocusing Schemes for Indoor Imaging with Unknown Walls

The quality and reliability of through-the-wall radar imagery is governed, among other things, by the knowledge of the wall characteristics. Ambiguity in wall characteristics has a two-fold effect. It smears and blurs the image, and also shifts the imaged target positions. In this paper, we consider the smearing effect and present an autofocusing technique, based on higher order statistics, which corrects for errors under unknown walls. This is achieved by tuning the wall variables until the sharpest image is obtained. Simulation results show that the proposed technique provides high-quality focused images with target locations in close proximity to the true target positions