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Parallel frequency radar via compressive sensing

  • Yanan You*
  • , Chunsheng Li
  • , Ze Yu
  • *Corresponding author for this work
  • Beihang University

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

Abstract

Traditional radar utilizes Shannon-Nyquist theorem for high bandwidth signal sampling, which induces the complicated system. Compressive sensing (CS) indicates that the compressible signal using a few measurements can be reconstructed by solving a convex optimization problem. Thus, the huge amount of data according to high Shannon-Nyquist rate is significantly reduced by compressive sensing. Parallel frequency radar theoretically cannot degrade the resolution compared with a traditional radar system and effectively reduces the sampling rate. In this paper, we focus on the data processing of the novel radar system. Basing on a sufficient structure, an algorithm of target scene reconstruction in pursuance of compressive sensing applied to the novel radar is proposed. Several simulations demonstrate the feasibility and the superiority of parallel frequency radar via compressive sensing.

Original languageEnglish
Title of host publication2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2696-2699
Number of pages4
ISBN (Print)9781457710056
DOIs
StatePublished - 2011
Event2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Vancouver, BC, Canada
Duration: 24 Jul 201129 Jul 2011

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
ISSN (Print)2153-6996
ISSN (Electronic)2153-7003

Conference

Conference2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011
Country/TerritoryCanada
CityVancouver, BC
Period24/07/1129/07/11

Keywords

  • Compressive sensing
  • parallel frequency radar
  • radar signal processing
  • simulations

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