Marco Salucci;Lorenzo Poli;Giorgio Gottardi;Giacomo Oliveri;Luca Tosi;Andrea Massa
{"title":"Microwave NDT/NDE Through Differential Bayesian Compressive Sensing","authors":"Marco Salucci;Lorenzo Poli;Giorgio Gottardi;Giacomo Oliveri;Luca Tosi;Andrea Massa","doi":"10.1109/OJIM.2024.3412205","DOIUrl":null,"url":null,"abstract":"This article deals with the nondestructive testing and evaluation (NDT/NDE) of dielectric structures through a sparseness-promoting probabilistic microwave imaging (MI) method. Prior information on both the unperturbed scenario and the class of imaged targets is profitably exploited to formulate the inverse scattering problem (ISP) at hand within a differential contrast source inversion (CSI) framework. The imaging process is then efficiently completed by applying a customized Bayesian compressive sensing (BCS) inversion strategy. Selected numerical and experimental results are provided to assess the effectiveness of the proposed imaging method also in comparison with competitive state-of-the-art alternatives.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"3 ","pages":"1-15"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10552809","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Instrumentation and Measurement","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10552809/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article deals with the nondestructive testing and evaluation (NDT/NDE) of dielectric structures through a sparseness-promoting probabilistic microwave imaging (MI) method. Prior information on both the unperturbed scenario and the class of imaged targets is profitably exploited to formulate the inverse scattering problem (ISP) at hand within a differential contrast source inversion (CSI) framework. The imaging process is then efficiently completed by applying a customized Bayesian compressive sensing (BCS) inversion strategy. Selected numerical and experimental results are provided to assess the effectiveness of the proposed imaging method also in comparison with competitive state-of-the-art alternatives.