{"title":"Near-field and far-field image reconstruction for an imperfectly conducting cylinder","authors":"Wei-Ting Chen, C. Chiu","doi":"10.1109/MMET.2000.890508","DOIUrl":null,"url":null,"abstract":"Comparison of image reconstruction by using near-field and far-field data for an imperfectly conducting cylinder is investigated. A conducting cylinder of unknown shape and conductivity scatters the incident wave in free space and the scattered near and far fields are measured. By using measured fields, the imaging problem is reformulated into an optimization problem and solved by the genetic algorithm. Numerical results show that the convergence speed and final reconstructed results by using near-field data are better than those obtained by using far-field data. Finally, it is worth noting that the present work provides not only comparative information but also quantitative information.","PeriodicalId":344401,"journal":{"name":"Conference Proceedings 2000 International Conference on Mathematical Methods in Electromagnetic Theory (Cat. No.00EX413)","volume":"29 10","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Proceedings 2000 International Conference on Mathematical Methods in Electromagnetic Theory (Cat. No.00EX413)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMET.2000.890508","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
Comparison of image reconstruction by using near-field and far-field data for an imperfectly conducting cylinder is investigated. A conducting cylinder of unknown shape and conductivity scatters the incident wave in free space and the scattered near and far fields are measured. By using measured fields, the imaging problem is reformulated into an optimization problem and solved by the genetic algorithm. Numerical results show that the convergence speed and final reconstructed results by using near-field data are better than those obtained by using far-field data. Finally, it is worth noting that the present work provides not only comparative information but also quantitative information.