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		<isbn>978-85-17-00066-9 (Internet)</isbn>
		<isbn>978-85-17-00065-2 (DVD)</isbn>
		<label>1456</label>
		<citationkey>GarciaKugaZana:2013:EfFiKa</citationkey>
		<title>Eficiência do Filtro de Kalman Unscented na estimação de atitude utilizando dados reais do satélite CBERS</title>
		<format>DVD, Internet.</format>
		<year>2013</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>393 KiB</size>
		<author>Garcia, Roberta Veloso,</author>
		<author>Kuga, Helio Koiti,</author>
		<author>Zanardi, Maria Cecília França de Paula Santos,</author>
		<resumeid></resumeid>
		<resumeid>8JMKD3MGP5W/3C9JHC9</resumeid>
		<group></group>
		<group>DMC-ETE-INPE-MCTI-GOV-BR</group>
		<affiliation></affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>rvelosogarcia@yahoo.com.br</electronicmailaddress>
		<editor>Epiphanio, José Carlos Neves,</editor>
		<editor>Galvão, Lênio Soares,</editor>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 16 (SBSR)</conferencename>
		<conferencelocation>Foz do Iguaçu</conferencelocation>
		<date>13-18 abr. 2013</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>2241-2249</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>The aim of this work is to compare the performance of the unscented Kalman filter (UKF) with the extended Kalman filter (EKF) in the attitude estimation nonlinear problems when the filters are subject to inaccurate initial conditions. For nonlinear systems the unscented Kalman filter uses a carefully selected set of sample points to more accurately map the probability distribution than the linearization of the standard extended Kalman filter, leading to faster convergence from inaccurate initial conditions in attitude estimation problems. In this study, the attitude of a satellite is estimated, simulating real time conditions using real data supplied by gyroscopes, infrared Earth sensors and digital Sun sensors. These sensors are on board the CBERS-2 satellite and the measurements were collected by the Satellite Control Centre of INPE. The satellite attitude is described by Euler angles, due to its easy geometric interpretation and the filter formulation is based on standard attitude-vector measurements using a gyro-based model for attitude propagation. Then by the degraded initial conditions it is possible to conclude that UKF is more efficient and accuracy than EKF. In relation with the process time, the UKF is competitive because although it demands a more time for the estimation process, the CPU time isn´t proportional to the generated sigma-points number. In the same way UKF can be applied in real time problem.</abstract>
		<area>SRE</area>
		<type>CBERS: Avaliação e Aplicações</type>
		<language>pt</language>
		<targetfile>p1456.pdf</targetfile>
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