Point and Beam-Sparse Radio Astronomical Source Recovery Using Non-Negative Least Squares

S. Naghibzadeh, Ahmad Mouri Sardarabadi, A.J. van der Veen

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)


A simple and novel algorithm for source recovery based on array data measurements in radio astronomy is proposed. Considering that a radioastronomical image is composed of both point sources and extended emissions, prior information on the images, namely non-negativity and substantial black background are taken into account to choose source representation basis functions. Dirac delta functions are chosen to represent point sources and a Gaussian function approximated from the main beam of the antenna array is selected to capture the extended emissions. We apply the non-negative least squares (NNLS) algorithm to estimate the basis coefficients. It is shown that the sparsity promoted by the NNLS algorithm based on the chosen basis functions results in a super-resolution (finer resolution than prescribed by the main beam of the antenna array pattern) estimate for the point sources and smooth recovery for the extended emissions.
Original languageEnglish
Title of host publication2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)
Place of PublicationPiscataway, NJ
Number of pages5
ISBN (Electronic)978-1-5090-2103-1
Publication statusPublished - 19 Sep 2016
Event2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM - Rio de Janeiro, Brazil
Duration: 10 Jul 201613 Jul 2016
Conference number: 9


Conference2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM
Abbreviated titleSAM
CityRio de Janeiro
Internet address


  • non-negative least squares
  • Array signal processing
  • image formation
  • interferometry
  • regularization
  • radio astronomy

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