relation: http://www.eledia.org/students-reports/795/
title: Robust Diagnosis of Microstrip Planar Phased Arrays Through a 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 radiators in real microstrip patches planar phased arrays. Towards this goal, the diagnosis problem at hand is formulated within a probabilistic compressive sensing (CS) framework in order to avoid the fulfillment of the restricted isometry property (RIP) by the involved measurement operator. A customized Bayesian CS solution approach is then developed to yield robust and reliable guesses of the antenna under test (AUT) status by also taking into account all mutual coupling effects arising in realistic operative conditions. Some numerical benchmarks are shown to assess the effectiveness of the proposed diagnosis tool when considering a variation of the antenna size and failure rate, as well as a change of the amount of noise on processed far-field data.
publisher: ELEDIA Research Center - University of Trento
date: 2019
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/795/1/Robust_Diagnosis_of_Microstrip_Planar_Phased_Arrays_Through_a_Compressive_Sensing_Approach.v2.pdf
identifier:   SALUCCI, Marco and GELMINI, Angelo and OLIVERI, Giacomo and MASSA, Andrea  (2019) Robust Diagnosis of Microstrip Planar Phased Arrays Through a Compressive Sensing Approach.  Technical Report. ELEDIA Research Center - University of Trento.