%0 Report
%9 Technical Report
%A Carlin, M.
%A Rocca, P.
%A Oliveri, G.
%A Massa, A.
%D 2016
%F elediasc12:701
%K Compressive Sensing, Direction-of-Arrival, Array Synthesis, Support Vector Machine, Inverse Scattering.
%T Bayesian Compressive Sensing-based Method for Directions-of-Arrival Estimation
%U http://www.eledia.org/students-reports/701/
%X In this report, the estimation of the directions of arrival (DoAs) of narrow-band signals impinging on a linear antenna array is addressed within the Bayesian compressive sensing (BCS) framework. Unlike several state-of-the-art approaches, the voltages at the output of the receiving sensors are directly used to determine the DoAs of the signals thus avoiding the computation of the correlation matrix. Towards this end, the estimation problem is properly formulated to enforce the sparsity of the solution in the linear relationships between output voltages (i.e., the problem data) and the unknown DoAs. A careful calibration of the BCS parameters is reported in the report after the problem formulation.