This paper investigates the feasibility of three image reconstruction algorithms for Ultra Wideband (UWB) signals in applications of detection and localization of human targets behind obstructing surfaces. The image reconstruction algorithms are represented by unfocused SAR (Synthetic Aperture Radar), focused SAR and Radon transform based tomographic method. Due to the focusing effect obtained by applying a quadratic phase correction, the best performance is obtained if the measured signals are processed using the focused SAR algorithm.

Wideband (WB) and ultrawideband (UWB) systems combined with multiple-input multiple-output (MIMO) technology increase both the systems performances and the complexity of the channel models required to evaluate their capabilities. Because in real scenarios waves propagate nonisotropically, the accuracy of the channel model is increased if nonisotropic propagation is considered. The channel bandwidth is the key term in the evaluation process of these systems because large bandwidths introduce frequency selectivity, a unique phenomenon of WB and UWB systems with more complexity in the latter case. This is due to the fact that, unlike WB technology in which the propagating signal is the only affected parameter by the frequency selectivity, in the UWB case, this phenomenon also affects the antenna propagation pattern (APP). In this paper, we developed a novel channel model based on the statistical analysis of two-dimensional cross correlation functions (CCFs) of WB/UWB MIMO nonisotropic channels. A mathematical solution to assess the frequency selective behavior of the UWB APP is also presented. The CCF reveals how the power spectral density (PSD) of the channel is influenced by bandwidth, nonisotropic propagation, and APP.