relation: http://www.eledia.org/students-reports/870/
title: Near-Field Antenna Characterization Through a Compressive Sensing Based Approach
creator: Salucci, Marco
creator: Anselmi, Nicola
creator: Massa, Andrea
subject: A WC Next Generation Wireless Communications
subject: M CS Compressive Sensing
description: A novel probabilistic sparsity-promoting method for robust near-field (NF) antenna characterization is proposed. It leverages on the measurements-by-design (MebD) paradigm, and it exploits some a priori information on the antenna under test (AUT) to generate an overcomplete representation basis. Accordingly, the problem at hand is reformulated in a compressive sensing (CS) framework as the retrieval of a maximally sparse distribution (with respect to the overcomplete basis) from a reduced set of measured data, and then, it is solved by means of a Bayesian strategy. Representative numerical results are presented to, also comparatively, assess the effectiveness of the proposed approach in reducing the “burden/cost” of the acquisition process and mitigate (possible) truncation errors when dealing with space-constrained probing systems.
publisher: ELEDIA Research Center - University of Trento
date: 2019
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/870/1/Near-Field_Antenna_Characterization_Through_a_Compressive_Sensing_Based_Approach.pdf
identifier:   Salucci, Marco and Anselmi, Nicola and Massa, Andrea  (2019) Near-Field Antenna Characterization Through a Compressive Sensing Based Approach.  Technical Report. ELEDIA Research Center - University of Trento.