%0 Report
%9 Technical Report
%A Anselmi, N.
%A Oliveri, G.
%A Hannan, M.
%A Salucci, M.
%A Massa, A.
%D 2017
%F elediasc12:742
%K Inverse Scattering (IS), Bayesian Compressive Sensing (BCS), Microwave Imaging, First Order Born Approximation
%T Innovative Alphabet‐Based Bayesian Compressive Sensing Technique for Imaging Targets with Arbitrary Shape
%U http://www.eledia.org/students-reports/742/
%X In this work an innovative two-dimensional (2D) microwave imaging technique exploiting Bayesian Compressive Sensing (BCS) and a wavelet-based alphabet for representing the problem unknowns is dealt with. The proposed approach is based on the generalization of the sparsity concept, extending the range of applicability of BCS-based inverse scattering (IS) techniques to objects with arbitrary shape and dimensions. A set of BCS reconstructions is performed considering different expansion bases in the alphabet, without the need for a-priori knowledge about the unknown scatterers. Then, the best reconstruction is recognized as that minimizing the number of non-null retrieved coefficients (i.e., the sparsest one). In order to verify the effectiveness of the proposed imaging technique, a set of representative numerical benchmarks is presented. Some comparisons with state-of-the-art IS techniques are presented, as well.