Baozhu Li, J. Yao, W. Ke, Wanchun Tang, M. Salucci, P. Rocca
{"title":"Total-Variation Compressive Sensing Based on Hybrid Sequential Experimental Design for Field Reconstruction","authors":"Baozhu Li, J. Yao, W. Ke, Wanchun Tang, M. Salucci, P. Rocca","doi":"10.23919/ACES48530.2019.9060585","DOIUrl":null,"url":null,"abstract":"An innovative approach for the two-dimensional (2D) far-field strength reconstruction from a reduced number of measurements without any prior knowledge on the source antenna is proposed. The developed methodology is based on the effective integration of a sequential experimental design (SED) strategy with a total variation compressive sensing (TV-CS) technique. Thanks to the SED, more samples are generated near highly non-linear regions of the field distribution, resulting in a more accurate reconstruction by means of the TV-CS. A set of numerical experiments is provided to assess the potentialities and features of the proposed method.","PeriodicalId":247909,"journal":{"name":"2019 International Applied Computational Electromagnetics Society Symposium - China (ACES)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Applied Computational Electromagnetics Society Symposium - China (ACES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ACES48530.2019.9060585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
An innovative approach for the two-dimensional (2D) far-field strength reconstruction from a reduced number of measurements without any prior knowledge on the source antenna is proposed. The developed methodology is based on the effective integration of a sequential experimental design (SED) strategy with a total variation compressive sensing (TV-CS) technique. Thanks to the SED, more samples are generated near highly non-linear regions of the field distribution, resulting in a more accurate reconstruction by means of the TV-CS. A set of numerical experiments is provided to assess the potentialities and features of the proposed method.