Batch and filter approaches to spacecraft sensor alignment estimation

Detalhes bibliográficos
Autor(a) principal: Zanardi, Maria Cecília [UNESP]
Data de Publicação: 1997
Outros Autores: Shuster, Malcolm D.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://adsabs.harvard.edu/full/1997ESASP.403..159Z
http://hdl.handle.net/11449/65234
Resumo: Two Kalman-filter formulations are presented for the estimation of spacecraft sensor misalignments from inflight data. In the first the sensor misalignments are part of the filter state variable; in the second the state vector contains only dynamical variables, but the sensitivities of the filter innovations to the misalignments are calculated within the Kalman filter. This procedure permits the misalignments to be estimated in batch mode as well as a much smaller dimension for the Kalman filter state vector. This results not only in a significantly smaller computational burden but also in a smaller sensitivity of the misalignment estimates to outliers in the data. Numerical simulations of the filter performance are presented.
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spelling Batch and filter approaches to spacecraft sensor alignment estimationTwo Kalman-filter formulations are presented for the estimation of spacecraft sensor misalignments from inflight data. In the first the sensor misalignments are part of the filter state variable; in the second the state vector contains only dynamical variables, but the sensitivities of the filter innovations to the misalignments are calculated within the Kalman filter. This procedure permits the misalignments to be estimated in batch mode as well as a much smaller dimension for the Kalman filter state vector. This results not only in a significantly smaller computational burden but also in a smaller sensitivity of the misalignment estimates to outliers in the data. Numerical simulations of the filter performance are presented.Department of Mathematics Univ. Estadual de São Paulo, 12500-000 Guarantinguetá (SP)Dept. Aerosp. Eng., Mechanics E. University of Florida, Gainesville, FL 32611-6250Universidade Estadual Paulista (Unesp)University of FloridaZanardi, Maria Cecília [UNESP]Shuster, Malcolm D.2014-05-27T11:18:17Z2014-05-27T11:18:17Z1997-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article159-166http://adsabs.harvard.edu/full/1997ESASP.403..159ZEuropean Space Agency, (Special Publication) ESA SP, n. 403, p. 159-166, 1997.0379-6566http://hdl.handle.net/11449/652342-s2.0-53442725067120496490032539Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEuropean Space Agency, (Special Publication) ESA SP0,125info:eu-repo/semantics/openAccess2021-10-23T11:51:30Zoai:repositorio.unesp.br:11449/65234Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T11:51:30Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Batch and filter approaches to spacecraft sensor alignment estimation
title Batch and filter approaches to spacecraft sensor alignment estimation
spellingShingle Batch and filter approaches to spacecraft sensor alignment estimation
Zanardi, Maria Cecília [UNESP]
title_short Batch and filter approaches to spacecraft sensor alignment estimation
title_full Batch and filter approaches to spacecraft sensor alignment estimation
title_fullStr Batch and filter approaches to spacecraft sensor alignment estimation
title_full_unstemmed Batch and filter approaches to spacecraft sensor alignment estimation
title_sort Batch and filter approaches to spacecraft sensor alignment estimation
author Zanardi, Maria Cecília [UNESP]
author_facet Zanardi, Maria Cecília [UNESP]
Shuster, Malcolm D.
author_role author
author2 Shuster, Malcolm D.
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
University of Florida
dc.contributor.author.fl_str_mv Zanardi, Maria Cecília [UNESP]
Shuster, Malcolm D.
description Two Kalman-filter formulations are presented for the estimation of spacecraft sensor misalignments from inflight data. In the first the sensor misalignments are part of the filter state variable; in the second the state vector contains only dynamical variables, but the sensitivities of the filter innovations to the misalignments are calculated within the Kalman filter. This procedure permits the misalignments to be estimated in batch mode as well as a much smaller dimension for the Kalman filter state vector. This results not only in a significantly smaller computational burden but also in a smaller sensitivity of the misalignment estimates to outliers in the data. Numerical simulations of the filter performance are presented.
publishDate 1997
dc.date.none.fl_str_mv 1997-12-01
2014-05-27T11:18:17Z
2014-05-27T11:18:17Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://adsabs.harvard.edu/full/1997ESASP.403..159Z
European Space Agency, (Special Publication) ESA SP, n. 403, p. 159-166, 1997.
0379-6566
http://hdl.handle.net/11449/65234
2-s2.0-5344272506
7120496490032539
url http://adsabs.harvard.edu/full/1997ESASP.403..159Z
http://hdl.handle.net/11449/65234
identifier_str_mv European Space Agency, (Special Publication) ESA SP, n. 403, p. 159-166, 1997.
0379-6566
2-s2.0-5344272506
7120496490032539
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv European Space Agency, (Special Publication) ESA SP
0,125
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 159-166
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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