Batch and filter approaches to spacecraft sensor alignment estimation
Autor(a) principal: | |
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Data de Publicação: | 1997 |
Outros Autores: | |
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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Repositório Institucional da UNESP |
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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:29462024-08-05T18:23:46.169742Repositório 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 |
|
_version_ |
1808128927155093504 |