relation: http://www.eledia.org/students-reports/793/
title: Diagnosis of Planar Phased Arrays Through a Probabilistic Compressive Sensing Approach
creator: SALUCCI, Marco
creator: GELMINI, Angelo
creator: OLIVERI, Giacomo
creator: MASSA, Andrea
subject: A WC Next Generation Wireless Communications
subject: M CS Compressive Sensing
description: This  work  deals  with  the  detection  of  faulty elements  in  planar  phased  antenna arrays  starting  from  far‐field  pattern  measurements. Owing  to  the  intrinsically sparse  nature  of  the  problem  unknowns  at  hand,  the diagnosis  problem  is formulated as a probabilistic Compressive Sensing (CS) one and it is effectively and efficiently solved through a customized Bayesian CS (BCS) solution approach. Some representative synthetic benchmarks are shown in order to verify the potentialities as well as the current limitations of the proposed BCS‐based diagnosis tool, as well as to assess its flexibility in dealing with arbitrary excitation taperings of the AUT.
publisher: ELEDIA Research Center - University of Trento
date: 2019
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/793/1/Diagnosis_of_Planar_Phased_Arrays_Through_a_Probabilistic_Compressive_Sensing_Approach.pdf
identifier:   SALUCCI, Marco and GELMINI, Angelo and OLIVERI, Giacomo and MASSA, Andrea  (2019) Diagnosis of Planar Phased Arrays Through a Probabilistic Compressive Sensing Approach.  Technical Report. ELEDIA Research Center - University of Trento.