Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Sba: Controle & Automação Sociedade Brasileira de Automatica |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592012000300003 |
Resumo: | A Rao-Blackwellized particle filter has been designed and its performance investigated in a simulated three-axis satellite testbed used for evaluating on-board attitude estimation and control algorithms. Vector measurements have been used to estimate attitude and angular rate and, additionally, a pseudo-measurement based on a low-pass filtered time-derivative of the vector measurements has been proposed to improve the filter performance. Conventional extended and unscented Kalman filters, and standard particle filtering have been compared with the proposed approach to gauge its performance regarding attitude and angular rate estimation accuracy, computational workload, convergence rate under uncertain initial conditions, and sensitivity to disturbances. Though a myriad of filters have been proposed in the past to tackle the problem of spacecraft attitude and angular rate estimation with vector observations, to the best knowledge of the authors the present Rao-Blackwellized particle filter is a novel approach that significantly reduces the computational load, provides an attractive convergence rate, and successfully preserves the performance of the standard particle filter when subjected to disturbances. |
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Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbedNonlinear filteringRao-Blackwellized particle filterextended Kalman filterunscented Kalman filternonlinear dynamicsA Rao-Blackwellized particle filter has been designed and its performance investigated in a simulated three-axis satellite testbed used for evaluating on-board attitude estimation and control algorithms. Vector measurements have been used to estimate attitude and angular rate and, additionally, a pseudo-measurement based on a low-pass filtered time-derivative of the vector measurements has been proposed to improve the filter performance. Conventional extended and unscented Kalman filters, and standard particle filtering have been compared with the proposed approach to gauge its performance regarding attitude and angular rate estimation accuracy, computational workload, convergence rate under uncertain initial conditions, and sensitivity to disturbances. Though a myriad of filters have been proposed in the past to tackle the problem of spacecraft attitude and angular rate estimation with vector observations, to the best knowledge of the authors the present Rao-Blackwellized particle filter is a novel approach that significantly reduces the computational load, provides an attractive convergence rate, and successfully preserves the performance of the standard particle filter when subjected to disturbances.Sociedade Brasileira de Automática2012-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592012000300003Sba: Controle & Automação Sociedade Brasileira de Automatica v.23 n.3 2012reponame:Sba: Controle & Automação Sociedade Brasileira de Automaticainstname:Sociedade Brasileira de Automática (SBA)instacron:SBA10.1590/S0103-17592012000300003info:eu-repo/semantics/openAccessChagas,Ronan Arraes JardimWaldmann,Jacqueseng2012-06-21T00:00:00Zoai:scielo:S0103-17592012000300003Revistahttps://www.sba.org.br/revista/PUBhttps://old.scielo.br/oai/scielo-oai.php||revista_sba@fee.unicamp.br1807-03450103-1759opendoar:2012-06-21T00:00Sba: Controle & Automação Sociedade Brasileira de Automatica - Sociedade Brasileira de Automática (SBA)false |
dc.title.none.fl_str_mv |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed |
title |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed |
spellingShingle |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed Chagas,Ronan Arraes Jardim Nonlinear filtering Rao-Blackwellized particle filter extended Kalman filter unscented Kalman filter nonlinear dynamics |
title_short |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed |
title_full |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed |
title_fullStr |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed |
title_full_unstemmed |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed |
title_sort |
Rao-Blackwellized particle filter with vector observations for satellite three-axis attitude estimation and control in a simulated testbed |
author |
Chagas,Ronan Arraes Jardim |
author_facet |
Chagas,Ronan Arraes Jardim Waldmann,Jacques |
author_role |
author |
author2 |
Waldmann,Jacques |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Chagas,Ronan Arraes Jardim Waldmann,Jacques |
dc.subject.por.fl_str_mv |
Nonlinear filtering Rao-Blackwellized particle filter extended Kalman filter unscented Kalman filter nonlinear dynamics |
topic |
Nonlinear filtering Rao-Blackwellized particle filter extended Kalman filter unscented Kalman filter nonlinear dynamics |
description |
A Rao-Blackwellized particle filter has been designed and its performance investigated in a simulated three-axis satellite testbed used for evaluating on-board attitude estimation and control algorithms. Vector measurements have been used to estimate attitude and angular rate and, additionally, a pseudo-measurement based on a low-pass filtered time-derivative of the vector measurements has been proposed to improve the filter performance. Conventional extended and unscented Kalman filters, and standard particle filtering have been compared with the proposed approach to gauge its performance regarding attitude and angular rate estimation accuracy, computational workload, convergence rate under uncertain initial conditions, and sensitivity to disturbances. Though a myriad of filters have been proposed in the past to tackle the problem of spacecraft attitude and angular rate estimation with vector observations, to the best knowledge of the authors the present Rao-Blackwellized particle filter is a novel approach that significantly reduces the computational load, provides an attractive convergence rate, and successfully preserves the performance of the standard particle filter when subjected to disturbances. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592012000300003 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592012000300003 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0103-17592012000300003 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Automática |
publisher.none.fl_str_mv |
Sociedade Brasileira de Automática |
dc.source.none.fl_str_mv |
Sba: Controle & Automação Sociedade Brasileira de Automatica v.23 n.3 2012 reponame:Sba: Controle & Automação Sociedade Brasileira de Automatica instname:Sociedade Brasileira de Automática (SBA) instacron:SBA |
instname_str |
Sociedade Brasileira de Automática (SBA) |
instacron_str |
SBA |
institution |
SBA |
reponame_str |
Sba: Controle & Automação Sociedade Brasileira de Automatica |
collection |
Sba: Controle & Automação Sociedade Brasileira de Automatica |
repository.name.fl_str_mv |
Sba: Controle & Automação Sociedade Brasileira de Automatica - Sociedade Brasileira de Automática (SBA) |
repository.mail.fl_str_mv |
||revista_sba@fee.unicamp.br |
_version_ |
1754824565681291264 |