Sparse Imaging of Building Layouts in Ultra-wideband Radar

Abstract

Ultra-WideBand (UWB) radar can reconstruct the layout of a building, providing rich information for detecting and locating humans in buildings. Traditional imaging methods suffer from serious sidelobes and location displacement of behind-the-wall target because of the influence of walls. Sparse recovery is introduced into the field of through-the-wall imaging to improve the imaging quality. However, the reconstruction probability of weak scattering targets is low in traditional methods. In this study, the combination of sparse recovery method and Coherence Factor (CF) weighting is proposed to improve the reconstruction probability of weak scattering targets inside a room. The quasi-establishment of the support set can be improved during sparse imaging by reducing the effect of the sidelobes of strong scattering targets with CF, ultimately enhancing the robustness of the sparse imaging of the building layout. A location correction model for multiple walls after sparse imaging is established, based on which the locating error of walls can be reduced with a low amount of calculation. The results of the measured data reveal that compared with the traditional generalized orthogonal matching pursuit method, the proposed methods can improve the reconstruction probability of weak scattering targets and reduce the locating error of the inner layouts of buildings to less than 10 cm.