{"title":"使用软收缩阈值的稀疏性微波逆散射","authors":"Hidayet Zaimaga, M. Lambert","doi":"10.1109/EUSIPCO.2016.7760268","DOIUrl":null,"url":null,"abstract":"A sparse nonlinear inverse scattering problem arising in microwave imaging is analyzed and numerically solved for retrieving dielectric contrast of region of interest from measured fields. The proposed approach is motivated by a Tikhonov functional incorporating a sparsity promoting l1-penalty term. The proposed iterative algorithm of soft shrinkage type enforces the sparsity constraint at each nonlinear iteration and provides an effective reconstructions of unknown (complex) dielectric profiles. The scheme produces sharp and good reconstruction of dielectric profiles in sparse domains and keeps its convergence during the reconstruction. Numerical results present the effectiveness and accuracy of the proposed method.","PeriodicalId":127068,"journal":{"name":"2016 24th European Signal Processing Conference (EUSIPCO)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Sparsity-enforced microwave inverse scattering using soft shrinkage thresholding\",\"authors\":\"Hidayet Zaimaga, M. Lambert\",\"doi\":\"10.1109/EUSIPCO.2016.7760268\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A sparse nonlinear inverse scattering problem arising in microwave imaging is analyzed and numerically solved for retrieving dielectric contrast of region of interest from measured fields. The proposed approach is motivated by a Tikhonov functional incorporating a sparsity promoting l1-penalty term. The proposed iterative algorithm of soft shrinkage type enforces the sparsity constraint at each nonlinear iteration and provides an effective reconstructions of unknown (complex) dielectric profiles. The scheme produces sharp and good reconstruction of dielectric profiles in sparse domains and keeps its convergence during the reconstruction. Numerical results present the effectiveness and accuracy of the proposed method.\",\"PeriodicalId\":127068,\"journal\":{\"name\":\"2016 24th European Signal Processing Conference (EUSIPCO)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 24th European Signal Processing Conference (EUSIPCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EUSIPCO.2016.7760268\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 24th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUSIPCO.2016.7760268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sparsity-enforced microwave inverse scattering using soft shrinkage thresholding
A sparse nonlinear inverse scattering problem arising in microwave imaging is analyzed and numerically solved for retrieving dielectric contrast of region of interest from measured fields. The proposed approach is motivated by a Tikhonov functional incorporating a sparsity promoting l1-penalty term. The proposed iterative algorithm of soft shrinkage type enforces the sparsity constraint at each nonlinear iteration and provides an effective reconstructions of unknown (complex) dielectric profiles. The scheme produces sharp and good reconstruction of dielectric profiles in sparse domains and keeps its convergence during the reconstruction. Numerical results present the effectiveness and accuracy of the proposed method.