Distributed image reconstruction for very large arrays in radio astronomy

André Ferrari; David Mary; Rémi Flamary; Cédric Richard

doi:10.1109/SAM.2014.6882424

Distributed image reconstruction for very large arrays in radio astronomy

André Ferrari
, David Mary
, Rémi Flamary
, Cédric Richard

Université de Nice

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Current and future radio interferometric arrays such as LOFAR and SKA are characterized by a paradox. Their large number of receptors (up to millions) allow theoretically unprecedented high imaging resolution. In the same time, the ultra massive amounts of samples makes the data transfer and computational loads (correlation and calibration) order of magnitudes too high to allow any currently existing image reconstruction algorithm to achieve, or even approach, the theoretical resolution. We investigate here decentralized and distributed image reconstruction strategies which select, transfer and process only a fraction of the total data. The loss in MSE incurred by the proposed approach is evaluated theoretically and numerically on simple test cases.

Original language	English
Title of host publication	2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Publisher	IEEE Computer Society
Pages	389-392
Number of pages	4
ISBN (Print)	9781479914814
DOIs	https://doi.org/10.1109/SAM.2014.6882424
Publication status	Published - 1 Jan 2014
Externally published	Yes
Event	2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 - A Coruna, Spain Duration: 22 Jun 2014 → 25 Jun 2014

Publication series

Name	Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (Electronic)	2151-870X

Conference

Conference	2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Country/Territory	Spain
City	A Coruna
Period	22/06/14 → 25/06/14

Access to Document

10.1109/SAM.2014.6882424

Cite this

Ferrari, A., Mary, D., Flamary, R., & Richard, C. (2014). Distributed image reconstruction for very large arrays in radio astronomy. In 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 (pp. 389-392). Article 6882422 (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop). IEEE Computer Society. https://doi.org/10.1109/SAM.2014.6882424

@inproceedings{1f00a2ccc28c422cb377b4f00da72c44,

title = "Distributed image reconstruction for very large arrays in radio astronomy",

abstract = "Current and future radio interferometric arrays such as LOFAR and SKA are characterized by a paradox. Their large number of receptors (up to millions) allow theoretically unprecedented high imaging resolution. In the same time, the ultra massive amounts of samples makes the data transfer and computational loads (correlation and calibration) order of magnitudes too high to allow any currently existing image reconstruction algorithm to achieve, or even approach, the theoretical resolution. We investigate here decentralized and distributed image reconstruction strategies which select, transfer and process only a fraction of the total data. The loss in MSE incurred by the proposed approach is evaluated theoretically and numerically on simple test cases.",

author = "Andr{\'e} Ferrari and David Mary and R{\'e}mi Flamary and C{\'e}dric Richard",

year = "2014",

month = jan,

day = "1",

doi = "10.1109/SAM.2014.6882424",

language = "English",

isbn = "9781479914814",

series = "Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop",

publisher = "IEEE Computer Society",

pages = "389--392",

booktitle = "2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014",

note = "2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 ; Conference date: 22-06-2014 Through 25-06-2014",

}

Ferrari, A, Mary, D, Flamary, R & Richard, C 2014, Distributed image reconstruction for very large arrays in radio astronomy. in 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014., 6882422, Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, IEEE Computer Society, pp. 389-392, 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014, A Coruna, Spain, 22/06/14. https://doi.org/10.1109/SAM.2014.6882424

Distributed image reconstruction for very large arrays in radio astronomy. / Ferrari, André; Mary, David; Flamary, Rémi et al.
2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014. IEEE Computer Society, 2014. p. 389-392 6882422 (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Distributed image reconstruction for very large arrays in radio astronomy

AU - Ferrari, André

AU - Mary, David

AU - Flamary, Rémi

AU - Richard, Cédric

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Current and future radio interferometric arrays such as LOFAR and SKA are characterized by a paradox. Their large number of receptors (up to millions) allow theoretically unprecedented high imaging resolution. In the same time, the ultra massive amounts of samples makes the data transfer and computational loads (correlation and calibration) order of magnitudes too high to allow any currently existing image reconstruction algorithm to achieve, or even approach, the theoretical resolution. We investigate here decentralized and distributed image reconstruction strategies which select, transfer and process only a fraction of the total data. The loss in MSE incurred by the proposed approach is evaluated theoretically and numerically on simple test cases.

AB - Current and future radio interferometric arrays such as LOFAR and SKA are characterized by a paradox. Their large number of receptors (up to millions) allow theoretically unprecedented high imaging resolution. In the same time, the ultra massive amounts of samples makes the data transfer and computational loads (correlation and calibration) order of magnitudes too high to allow any currently existing image reconstruction algorithm to achieve, or even approach, the theoretical resolution. We investigate here decentralized and distributed image reconstruction strategies which select, transfer and process only a fraction of the total data. The loss in MSE incurred by the proposed approach is evaluated theoretically and numerically on simple test cases.

U2 - 10.1109/SAM.2014.6882424

DO - 10.1109/SAM.2014.6882424

M3 - Conference contribution

AN - SCOPUS:84907401739

SN - 9781479914814

T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop

SP - 389

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BT - 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014

PB - IEEE Computer Society

T2 - 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014

Y2 - 22 June 2014 through 25 June 2014

ER -

Distributed image reconstruction for very large arrays in radio astronomy

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