Ricerc@Sapienza

This paper presents a procedure for reconstruction of spatially localized images from compressively sampled measurements making use of Bayesian priors. The contribution of this paper is twofold: firstly, we analytically derive the expected value of wavelet domain signal structures conditional to a suitably defined noisy estimate; secondly, we exploit such conditional expectation within a nonlinear estimation stage that is added to an iterative reconstruction algorithm at a very low computational cost.

In this paper a through the wall radar imaging (TWRI) system based on a step frequency radar is presented. The radar equation is used for assessing the system power budget and two algorithms, namely the delay and sum (DAS) and the range migration (RM) are used for the scenario reconstruction. The achieved results evidence the strong dependence of the radar-re-ceived power on the wall losses. A frequency of 4 GHz seems to be the maximum allowable for practical TWRI systems.