{"title":"Hybridized Contrast Source Inversion Method","authors":"Serhat Dinleyen, H. A. Ülkü","doi":"10.23919/URSIGASS51995.2021.9560551","DOIUrl":null,"url":null,"abstract":"A contrast source inversion based method, which hybridizes the cross-correlated contrast source inversion method (CC-CSIM) and multiplicative regularized contrast source inversion method (MR-CSIM) by applying them consecutively, is proposed for the solution of inverse scattering problems. The proposed method, called hybridized contrast source inversion method (H-CSIM), benefits the effective properties of MR-CSIM and CC-CSIM. A numerical example that demonstrates the robustness to noise, improved reconstruction accuracy, and convergence properties of the proposed method is presented.","PeriodicalId":152047,"journal":{"name":"2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/URSIGASS51995.2021.9560551","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
A contrast source inversion based method, which hybridizes the cross-correlated contrast source inversion method (CC-CSIM) and multiplicative regularized contrast source inversion method (MR-CSIM) by applying them consecutively, is proposed for the solution of inverse scattering problems. The proposed method, called hybridized contrast source inversion method (H-CSIM), benefits the effective properties of MR-CSIM and CC-CSIM. A numerical example that demonstrates the robustness to noise, improved reconstruction accuracy, and convergence properties of the proposed method is presented.