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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3RFK9HL
Repositorysid.inpe.br/mtc-m21c/2018/07.18.15.57
Last Update2021:02.23.12.40.08 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2018/07.18.15.57.39
Metadata Last Update2021:02.23.12.40.08 (UTC) simone
Secondary KeyINPE--PRE/
Citation KeyGarciaPardKuga:2018:CuKaFi
TitleNonlinear filtering for sequential spacecraft attitude estimation with real data: cubature kalman filter, unscented kalman filter and extended kalman filter
Year2018
Access Date2024, May 25
Secondary TypePRE CI
Number of Files1
Size65 KiB
2. Context
Author1 Garcia, Roberta Veloso
2 Pardal, C. Paula M.
3 Kuga, Hélio Koiti
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JHC9
Group1
2
3 DIDMC-CGETE-INPE-MCTIC-GOV-BR
Affiliation1 Universidade de São Paulo (USP)
2 Universidade de São Paulo (USP)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 robertagarcia@usp.br
2 paulapardal@usp.br
3 helio.kuga@inpe.br
Conference NameCospar Scientific Assembly, 42
Conference LocationPasadena, California
Date14-22 July
History (UTC)2018-07-18 15:58:03 :: simone -> administrator :: 2018
2019-01-04 16:57:07 :: administrator -> simone :: 2018
2019-01-07 09:54:15 :: simone -> administrator :: 2018
2021-02-11 18:14:16 :: administrator -> simone :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
AbstractThe purpose of this work is to analyze the performance of the Cubature Kalman Filter, Unscented Kalman Filter and Extended Kalman Filter estimators in the attitude estimation problem when submitted to real attitude sensors data. The Extended Kalman Filter (EKF) is the most used nonlinear filtering algorithm for the attitude estimation in real time. The EKF is the nonlinear version of the Kalman Filter which linearizes about an estimate of the current mean and covariance. However, when the filter is subjected to poor conditions, the linearization of the system may not be efficient and lead to an estimation of low accuracy and divergence of the filter. The Unscented Kalman Filter (UKF) is an algorithm that was developed in order to avoid the linearizations required by the EKF. Basically, the UKF uses a set of points chosen deterministically, called sigma-points, to capture the probability distribution and generalizes to nonlinear system without the burdensome analytic derivation as in the EKF. More recently, the Cubature Kalman Filter (CKF) was proposed as an alternative estimation algorithm for general nonlinear systems. The CKF, which builds on the numerical-integration perspective of Gaussian filters, employs a third-degree spherical-radical cubature rule to compute Gaussianweighted integrals, derivative-free nonlinear filtering algorithm with improved performance over the UKF in terms of estimation accuracy, numerical stability and computational costs. In this work, the application uses the real measurement data for orbit and attitude of the CBERS-2 (China Brazil Earth Resources Satellite) satellite. The attitude dynamical model is described by nonlinear equations involving the Euler angles. The attitude sensors available are two DSS (Digital Sun Sensors), two IRES (Infra-Red Earth Sensor), and one triad of mechanical gyros. The analyzes are based on the robustness of the filter, in relation to the precision, computational cost and convergence speed in attitude estimation. As the use of real data makes it impossible to compare the estimated results with the real attitude of the satellite, then the results obtained via EKF are taken as reference for comparison with the UKF and CKF. The results in this work show that, for the case studied in this article, the filters are very competitive and present advantages and disadvantages that should be evaluated according to the need of each problem.
AreaETES
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP3W34R/3RFK9HL
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W34R/3RFK9HL
Languageen
Target Filegarcia_nonlinear.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/446AF4B
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.49.46 2
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
Empty Fieldsarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url versiontype volume
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