RF Compressed Sensing Based Radar for 2-D Localization and Mapping

Prateek Nallabolu, Changzhi Li

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

1 Scopus citations

Abstract

This paper presents the simulation results of a radio frequency (RF) compressed sensing (CS) radar for 2-D localization and mapping. In contrast to many existing literatures, this paper deals with the RF front-end compressive sensing, which is achieved by illuminating the target scenario with pseudo random multi-beam radiation patterns. The spatial sparsity of the target frame enables the use of compressed sensing to recover the scene from fewer number of scans compared with a conventional beam scanning radar. Preliminary simulations are performed, and the results of the reconstructed target frame are presented.

Original languageEnglish
Title of host publicationIEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538673959
DOIs
StatePublished - May 2019
Event2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019 - Nanjing, China
Duration: May 6 2019May 8 2019

Publication series

NameIEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings

Conference

Conference2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019
CountryChina
CityNanjing
Period05/6/1905/8/19

Keywords

  • 2-D localization
  • compressed sensing
  • multi-beam radiation pattern
  • spatial sparsity

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