Principal Component Analysis (PCA) based compressive sensing millimeter wave imaging system

Min Liang, Ying Li, Mark A Neifeld, Hao Xin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Compressive sensing is a novel sampling/sensing paradigm that enables significant sampling and computation cost reduction for signals with sparse or compressible representation. With compressive sensing technique, the number of measurements needed for accomplishing a specific task can be greatly reduced compared to traditional methods when the signal is sparse in certain basis. The fundamental idea behind compressive sensing is that rather than sampling at high rate first and then compressing the sampled data, it would be much better to directly sample the data in a compressed format.

Original languageEnglish (US)
Title of host publication2015 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages341
Number of pages1
ISBN (Print)9781479978175
DOIs
StatePublished - Oct 21 2015
EventUSNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2015 - Vancouver, Canada
Duration: Jul 19 2015Jul 24 2015

Other

OtherUSNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2015
CountryCanada
CityVancouver
Period7/19/157/24/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Communication

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    Liang, M., Li, Y., Neifeld, M. A., & Xin, H. (2015). Principal Component Analysis (PCA) based compressive sensing millimeter wave imaging system. In 2015 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2015 - Proceedings (pp. 341). [7303625] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USNC-URSI.2015.7303625