Spectrum estimation using frequency shifting and decimation

Autores
Albert, Raymundo Jose; Galarza, Cecilia Gabriela
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Parametric spectral estimation techniques are widely used to estimate the parameters of sums of complex sinusoids corrupted by noise. In this work, we show that the numerical stability of the estimated frequencies not only depends on the size of the amplitudes associated to the real frequencies, but also to the distance among frequencies. Therefore, for closely spaced frequencies, the estimates are vulnerable to large deviate from their true values. To overcome this problem we propose a strategy to artificially increase the frequency separation by downsampling the base band equivalent of the noisy signal before applying a spectral estimation technique. This methodology significantly improves the estimation performance especially in the low signal to noise ratio regime. The performance of the technique is assessed in terms of the root mean square error and it is compared to results obtained in previous publications.
Fil: Albert, Raymundo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; Argentina
Fil: Galarza, Cecilia Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; Argentina
Materia
SPECTRUM ESTIMATION
MULTIRATE PROCESSING
NATURAL FREQUENCIES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/155659

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spelling Spectrum estimation using frequency shifting and decimationAlbert, Raymundo JoseGalarza, Cecilia GabrielaSPECTRUM ESTIMATIONMULTIRATE PROCESSINGNATURAL FREQUENCIEShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Parametric spectral estimation techniques are widely used to estimate the parameters of sums of complex sinusoids corrupted by noise. In this work, we show that the numerical stability of the estimated frequencies not only depends on the size of the amplitudes associated to the real frequencies, but also to the distance among frequencies. Therefore, for closely spaced frequencies, the estimates are vulnerable to large deviate from their true values. To overcome this problem we propose a strategy to artificially increase the frequency separation by downsampling the base band equivalent of the noisy signal before applying a spectral estimation technique. This methodology significantly improves the estimation performance especially in the low signal to noise ratio regime. The performance of the technique is assessed in terms of the root mean square error and it is compared to results obtained in previous publications.Fil: Albert, Raymundo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; ArgentinaFil: Galarza, Cecilia Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; ArgentinaInstitution of Engineering and Technology2020-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/155659Albert, Raymundo Jose; Galarza, Cecilia Gabriela; Spectrum estimation using frequency shifting and decimation; Institution of Engineering and Technology; Iet Signal Processing; 14; 3; 4-2020; 134-1411751-9675CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2019.0306info:eu-repo/semantics/altIdentifier/doi/10.1049/iet-spr.2019.0306info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:23:12Zoai:ri.conicet.gov.ar:11336/155659instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:23:13.086CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Spectrum estimation using frequency shifting and decimation
title Spectrum estimation using frequency shifting and decimation
spellingShingle Spectrum estimation using frequency shifting and decimation
Albert, Raymundo Jose
SPECTRUM ESTIMATION
MULTIRATE PROCESSING
NATURAL FREQUENCIES
title_short Spectrum estimation using frequency shifting and decimation
title_full Spectrum estimation using frequency shifting and decimation
title_fullStr Spectrum estimation using frequency shifting and decimation
title_full_unstemmed Spectrum estimation using frequency shifting and decimation
title_sort Spectrum estimation using frequency shifting and decimation
dc.creator.none.fl_str_mv Albert, Raymundo Jose
Galarza, Cecilia Gabriela
author Albert, Raymundo Jose
author_facet Albert, Raymundo Jose
Galarza, Cecilia Gabriela
author_role author
author2 Galarza, Cecilia Gabriela
author2_role author
dc.subject.none.fl_str_mv SPECTRUM ESTIMATION
MULTIRATE PROCESSING
NATURAL FREQUENCIES
topic SPECTRUM ESTIMATION
MULTIRATE PROCESSING
NATURAL FREQUENCIES
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Parametric spectral estimation techniques are widely used to estimate the parameters of sums of complex sinusoids corrupted by noise. In this work, we show that the numerical stability of the estimated frequencies not only depends on the size of the amplitudes associated to the real frequencies, but also to the distance among frequencies. Therefore, for closely spaced frequencies, the estimates are vulnerable to large deviate from their true values. To overcome this problem we propose a strategy to artificially increase the frequency separation by downsampling the base band equivalent of the noisy signal before applying a spectral estimation technique. This methodology significantly improves the estimation performance especially in the low signal to noise ratio regime. The performance of the technique is assessed in terms of the root mean square error and it is compared to results obtained in previous publications.
Fil: Albert, Raymundo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; Argentina
Fil: Galarza, Cecilia Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; Argentina
description Parametric spectral estimation techniques are widely used to estimate the parameters of sums of complex sinusoids corrupted by noise. In this work, we show that the numerical stability of the estimated frequencies not only depends on the size of the amplitudes associated to the real frequencies, but also to the distance among frequencies. Therefore, for closely spaced frequencies, the estimates are vulnerable to large deviate from their true values. To overcome this problem we propose a strategy to artificially increase the frequency separation by downsampling the base band equivalent of the noisy signal before applying a spectral estimation technique. This methodology significantly improves the estimation performance especially in the low signal to noise ratio regime. The performance of the technique is assessed in terms of the root mean square error and it is compared to results obtained in previous publications.
publishDate 2020
dc.date.none.fl_str_mv 2020-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/155659
Albert, Raymundo Jose; Galarza, Cecilia Gabriela; Spectrum estimation using frequency shifting and decimation; Institution of Engineering and Technology; Iet Signal Processing; 14; 3; 4-2020; 134-141
1751-9675
CONICET Digital
CONICET
url http://hdl.handle.net/11336/155659
identifier_str_mv Albert, Raymundo Jose; Galarza, Cecilia Gabriela; Spectrum estimation using frequency shifting and decimation; Institution of Engineering and Technology; Iet Signal Processing; 14; 3; 4-2020; 134-141
1751-9675
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2019.0306
info:eu-repo/semantics/altIdentifier/doi/10.1049/iet-spr.2019.0306
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institution of Engineering and Technology
publisher.none.fl_str_mv Institution of Engineering and Technology
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432