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

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

doi:10.1109/sam.2016.7569681

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

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

Signal Processing Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

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 language	English
Title of host publication	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)
Place of Publication	Piscataway, NJ
Pages	1-5
Number of pages	5
ISBN (Electronic)	978-1-5090-2103-1
DOIs	https://doi.org/10.1109/sam.2016.7569681
Publication status	Published - 19 Sept 2016
Event	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM - Rio de Janeiro, Brazil Duration: 10 Jul 2016 → 13 Jul 2016 Conference number: 9 https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=35132 http://delamare.cetuc.puc-rio.br/sam2016/index.html

Conference

Conference	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM
Abbreviated title	SAM
Country/Territory	Brazil
City	Rio de Janeiro
Period	10/07/16 → 13/07/16
Internet address	https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=35132 http://delamare.cetuc.puc-rio.br/sam2016/index.html

Keywords

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

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10.1109/sam.2016.7569681

Cite this

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title = "Point and Beam-Sparse Radio Astronomical Source Recovery Using Non-Negative Least Squares",

abstract = "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.",

keywords = "non-negative least squares, Array signal processing, image formation, interferometry, regularization, radio astronomy",

author = "S. Naghibzadeh and {Mouri Sardarabadi}, Ahmad and Veen, {A.J. van der}",

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doi = "10.1109/sam.2016.7569681",

language = "English",

pages = "1--5",

booktitle = "2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)",

note = "2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM, SAM ; Conference date: 10-07-2016 Through 13-07-2016",

url = "https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=35132, http://delamare.cetuc.puc-rio.br/sam2016/index.html",

}

Naghibzadeh, S, Mouri Sardarabadi, A & Veen, AJVD 2016, Point and Beam-Sparse Radio Astronomical Source Recovery Using Non-Negative Least Squares. in 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). Piscataway, NJ, pp. 1-5, 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM, Rio de Janeiro, Brazil, 10/07/16. https://doi.org/10.1109/sam.2016.7569681

Point and Beam-Sparse Radio Astronomical Source Recovery Using Non-Negative Least Squares. / Naghibzadeh, S.; Mouri Sardarabadi, Ahmad; Veen, A.J. van der.
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). Piscataway, NJ, 2016. p. 1-5.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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T1 - Point and Beam-Sparse Radio Astronomical Source Recovery Using Non-Negative Least Squares

AU - Naghibzadeh, S.

AU - Mouri Sardarabadi, Ahmad

AU - Veen, A.J. van der

N1 - Conference code: 9

PY - 2016/9/19

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N2 - 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.

AB - 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.

KW - non-negative least squares

KW - Array signal processing

KW - image formation

KW - interferometry

KW - regularization

KW - radio astronomy

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M3 - Conference contribution

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BT - 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)

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T2 - 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM

Y2 - 10 July 2016 through 13 July 2016

ER -

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

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