Compressive Sensing: Analysis of Signals in Radio Astronomy

The compressive sensing (CS) theory says that for some kind of signals there is no need to keep or transfer all the data acquired accordingly to the Nyquist criterion. In this work we investigate if the CS approach is applicable for recording and analysis of radio astronomy (RA) signals. Since CS me...

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Main Authors: Gaigals G., Greitāns M., Andziulis A.
Format: Article
Language:English
Published: De Gruyter 2013-12-01
Series:Open Astronomy
Subjects:
Online Access:https://doi.org/10.1515/astro-2017-0165
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spelling doaj-1840f9e0f62d4083896566ecc75c37c52021-09-06T19:40:12ZengDe GruyterOpen Astronomy2543-63762013-12-0122434736110.1515/astro-2017-0165astro-2017-0165Compressive Sensing: Analysis of Signals in Radio AstronomyGaigals G.0Greitāns M.1Andziulis A.2 Engineering Research Institute “Ventspils International Radio Astronomy Centre”, Ventspils University College, Inženieru iela 101, Ventspils, LV-3601, Latvia Institute of Electronics and Computer Science, 14 Dzerbenes St., Riga, LV-1006, Latvia Klaipėda University, Manto 84, Klaipėda, LT-92294, LithuaniaThe compressive sensing (CS) theory says that for some kind of signals there is no need to keep or transfer all the data acquired accordingly to the Nyquist criterion. In this work we investigate if the CS approach is applicable for recording and analysis of radio astronomy (RA) signals. Since CS methods are applicable for the signals with sparse (and compressible) representations, the compressibility of RA signals is verified. As a result, we identify which RA signals can be processed using CS, find the parameters which can improve or degrade CS application to RA results, describe the optimum way how to perform signal filtering in CS applications. Also, a range of virtual LabVIEW instruments are created for the signal analysis with the CS theory.https://doi.org/10.1515/astro-2017-0165methods: radio astronomy signals: compressive sensing, sparsity, filtering
collection DOAJ
language English
format Article
sources DOAJ
author Gaigals G.
Greitāns M.
Andziulis A.
spellingShingle Gaigals G.
Greitāns M.
Andziulis A.
Compressive Sensing: Analysis of Signals in Radio Astronomy
Open Astronomy
methods: radio astronomy signals: compressive sensing, sparsity, filtering
author_facet Gaigals G.
Greitāns M.
Andziulis A.
author_sort Gaigals G.
title Compressive Sensing: Analysis of Signals in Radio Astronomy
title_short Compressive Sensing: Analysis of Signals in Radio Astronomy
title_full Compressive Sensing: Analysis of Signals in Radio Astronomy
title_fullStr Compressive Sensing: Analysis of Signals in Radio Astronomy
title_full_unstemmed Compressive Sensing: Analysis of Signals in Radio Astronomy
title_sort compressive sensing: analysis of signals in radio astronomy
publisher De Gruyter
series Open Astronomy
issn 2543-6376
publishDate 2013-12-01
description The compressive sensing (CS) theory says that for some kind of signals there is no need to keep or transfer all the data acquired accordingly to the Nyquist criterion. In this work we investigate if the CS approach is applicable for recording and analysis of radio astronomy (RA) signals. Since CS methods are applicable for the signals with sparse (and compressible) representations, the compressibility of RA signals is verified. As a result, we identify which RA signals can be processed using CS, find the parameters which can improve or degrade CS application to RA results, describe the optimum way how to perform signal filtering in CS applications. Also, a range of virtual LabVIEW instruments are created for the signal analysis with the CS theory.
topic methods: radio astronomy signals: compressive sensing, sparsity, filtering
url https://doi.org/10.1515/astro-2017-0165
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AT greitansm compressivesensinganalysisofsignalsinradioastronomy
AT andziulisa compressivesensinganalysisofsignalsinradioastronomy
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