Title :
Imaging sparse scatterers through a multi-frequency CS approach
Author :
Poli, Lorenzo ; Oliveri, G. ; Manica, Luca ; Massa, A.
Author_Institution :
ELEDIA Res. Center @ DISI, Univ. of Trento, Trento, Italy
Abstract :
In this paper an inverse scattering technique based on the multi-task Bayesian Compressive Sensing is presented within a multi-frequency framework. After recasting the problem in a probabilistic sense, the solution to the imaging problem is determined by means of an efficient Relevant Vector Machine coupled with a contrast source inversion procedure. Selected numerical results are discussed to assess and compare the efficiency and robustness of the proposed strategy with respect to the state-of-the-art techniques.
Keywords :
Bayes methods; compressed sensing; electrical engineering computing; electromagnetic wave scattering; probability; support vector machines; contrast source inversion procedure; imaging sparse scatterers; inverse scattering technique; multifrequency CS approach; multifrequency framework; multitask Bayesian compressive sensing; relevant vector machine; Antennas; Bayes methods; Compressed sensing; Dielectrics; Image reconstruction; Imaging; Signal to noise ratio; Multi-Task Bayesian Compressive Sampling; inverse scattering; multi-frequency microwave imaging;
Conference_Titel :
Antennas and Propagation (EuCAP), 2014 8th European Conference on
Conference_Location :
The Hague
DOI :
10.1109/EuCAP.2014.6901704