Full Reconstruction of Focal-Field Distribution Using Compressed Sensing

Decheng Wu, Hailin Cao, Zhoujian Chen, Lu Tao, Jing Liu, Chengzhuo Zhu, Yantao Yu, Jin Fan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

A full reconstruction method of focal-field distribution using compressed sensing (CS) is presented. Exploring focal-field distribution characteristics, a proper sparsifying basis is constructed via the Kronecker product. The full distribution data can be obtained by solving a l1-norm minimization problem. Three scenarios are set up to verify the effectiveness of the proposed method. Simulation results demonstrate that the focal-field distribution can be relatively accurate reconstructed with a few array feeds.

Original languageEnglish
Title of host publication2017 IEEE Antennas and Propagation Society International Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages571-572
Number of pages2
ISBN (Electronic)9781538632840
DOIs
StatePublished - 18 Oct 2017
Externally publishedYes
Event2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017 - San Diego, United States
Duration: 9 Jul 201714 Jul 2017

Publication series

Name2017 IEEE Antennas and Propagation Society International Symposium, Proceedings
Volume2017-January

Conference

Conference2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017
Country/TerritoryUnited States
CitySan Diego
Period9/07/1714/07/17

Keywords

  • Compressed sensing
  • Focal-field distribution

Fingerprint

Dive into the research topics of 'Full Reconstruction of Focal-Field Distribution Using Compressed Sensing'. Together they form a unique fingerprint.

Cite this