relation: http://www.eledia.org/students-reports/701/
title: Bayesian Compressive Sensing-based Method for Directions-of-Arrival Estimation
creator: Carlin, M.
creator: Rocca, P.
creator: Oliveri, G.
creator: Massa, A.
subject: M CS Compressive Sensing
subject: M LBE Learning-by-Example Methods
description: 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.
publisher: University of Trento
date: 2016
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/701/1/Bayesian_Compressive_Sensing-based_Method_for_Directions-of-Arrival_Estimation.v2.pdf
identifier:   Carlin, M. and Rocca, P. and Oliveri, G. and Massa, A.  (2016) Bayesian Compressive Sensing-based Method for Directions-of-Arrival Estimation.  Technical Report. University of Trento.