Towards more accurate radio telescope images

Nezihe Merve Gürel, Paul Hurley, Matthieu Simeoni

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

1 Citation (Scopus)

Abstract

![CDATA[Radio interferometry usually compensates for high levels of noise in sensor/antenna electronics by throwing data and energy at the problem: observe longer, then store and process it all. We propose instead a method to remove the noise explicitly before imaging. To this end, we developed an algorithm that first decomposes the instances of antenna correlation matrix, the so-called visibility matrix, into additive components using Singular Spectrum Analysis and then cluster these components using graph Laplacian matrix. We show through simulation the potential for radio astronomy, in particular, illustrating the benefit for LOFAR, the low frequency array in Netherlands. Least-squares images are estimated with far higher accuracy with low computation cost without the need for long observation time.]]
Original languageEnglish
Title of host publicationProceedings of the 31st IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2018), 18-22 June 2018, Salt Lake City, Utah
PublisherIEEE
Pages1983-1985
Number of pages3
ISBN (Print)9781538661000
DOIs
Publication statusPublished - 2018
EventIEEE Computer Society Conference on Computer Vision and Pattern Recognition -
Duration: 18 Jun 2018 → …

Publication series

Name
ISSN (Print)2160-7516

Conference

ConferenceIEEE Computer Society Conference on Computer Vision and Pattern Recognition
Period18/06/18 → …

Keywords

  • computer vision
  • radio astronomy
  • radio telescopes
  • spectrum analysis

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