The Extended H∞ Particle Filter for Attitude Estimation Applied to Remote Sensing Satellite CBERS-4

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Autor(es): dc.contributorSetor Leste (Gama)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorPACT-
Autor(es): dc.contributorNational Institute for Space Research (INPE)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Federal do ABC (UFABC)-
Autor(es): dc.creatorSilva, William Reis-
Autor(es): dc.creatorGarcia, Roberta Veloso-
Autor(es): dc.creatorPardal, Paula C. P. M.-
Autor(es): dc.creatorKuga, Hélio Koiti-
Autor(es): dc.creatorZanardi, Maria Cecília F. P. S.-
Autor(es): dc.creatorBaroni, Leandro-
Data de aceite: dc.date.accessioned2025-08-21T20:57:47Z-
Data de disponibilização: dc.date.available2025-08-21T20:57:47Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-08-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/rs15164052-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/297024-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/297024-
Descrição: dc.descriptionAn extension of the linear (Formula presented.) filter, presented here as the extended (Formula presented.) particle filter (E (Formula presented.) PF), is used in this work for attitude estimation, which presents a process and measurement model with nonlinear functions. The simulations implemented use orbit and attitude data from CBERS-4 (China–Brazil Earth Resources Satellite-4), making use of the robustness characteristics of the (Formula presented.) filter. The CBERS-4 is the fifth satellite of an advantageous international scientific interaction between Brazil and China for the development of remote sensing satellites used for strategic application in monitoring water resources and controlling deforestation in the Legal Amazon. In the extended (Formula presented.) particle filter (E (Formula presented.) PF) the nature of the system, composed of dynamics and noises, seeks to degrade the state estimate. The E (Formula presented.) PF deals with this by aiming for robustness, using a performance parameter in its cost function, in addition to presenting an advantageous feature of using a reduced number of particles for state estimation. The justification for the application of this method is because the non-Gaussian uncertainties that appear in the attitude sensors impair the estimation process and the E (Formula presented.) PF minimizes in signal estimation the worst effects of disturbance signals without a priori knowledge of them, as shown in the results, in addition to presenting good precision within the prescribed requirements, with 100 particles representing a processing time 2.09 times less than the PF with 500 particles.-
Descrição: dc.descriptionUniversity of Brasilia (UnB) Área Especial de Indústria Projeção A Setor Leste (Gama), Gama Campus (FGA), DF-
Descrição: dc.descriptionLorena School of Engineering (EEL) University of São Paulo (USP), Estrada Municipal do Campinho, S/N. Ponte Nova, SP-
Descrição: dc.descriptionCollaborative Laboratory (CoLAB) Center of Engineering and Product Development (CEiiA) PACT, Rua Luís Adelino Fonseca, 1-
Descrição: dc.descriptionSpace Mechanics and Control Division (DMC) National Institute for Space Research (INPE), Av. dos Astronautas, 1758, Jardim da Granja, SP-
Descrição: dc.descriptionSão Paulo State University (UNESP), Campus Guaratinguetá (FEG), Av. Dr. Ariberto Pereira da Cunha, 333, Pedregulho, SP-
Descrição: dc.descriptionEngineering Modeling and Applied Social Sciences Center (CECS) Federal University of ABC (UFABC), Av. dos Estados, 5001, Bangú, SP-
Descrição: dc.descriptionSão Paulo State University (UNESP), Campus Guaratinguetá (FEG), Av. Dr. Ariberto Pereira da Cunha, 333, Pedregulho, SP-
Idioma: dc.languageen-
Relação: dc.relationRemote Sensing-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectattitude estimation-
Palavras-chave: dc.subjectChina–Brazil Earth Resources Satellite-
Palavras-chave: dc.subjectextended H∞ particle filter-
Palavras-chave: dc.subjectnonlinear state estimation-
Palavras-chave: dc.subjectparticle filter-
Título: dc.titleThe Extended H∞ Particle Filter for Attitude Estimation Applied to Remote Sensing Satellite CBERS-4-
Tipo de arquivo: dc.typelivro digital-
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