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ARTIGO_ExtendedParticleFilter.pdf | 870,68 kB | Adobe PDF | View/Open |
Title: | The extended H∞ particle filter for attitude estimation applied to remote sensing satellite CBERS-4 |
Authors: | Silva, William Reis Garcia, Roberta Veloso Pardal, Paula C. P. M. Kuga, Hélio Koiti Zanardi, Maria Cecília F. P. S. Baroni, Leandro |
metadata.dc.identifier.orcid: | https://orcid.org/0000-0002-4843-0267 https://orcid.org/0000-0002-0633-6272 https://orcid.org/0000-0003-1046-6587 https://orcid.org/0000-0002-0259-0724 https://orcid.org/0000-0001-9940-2146 https://orcid.org/0000-0002-1078-7201 |
metadata.dc.contributor.affiliation: | University of Brasilia (UnB), Gama Campus (FGA) University of São Paulo (USP), Lorena School of Engineering (EEL) Center of Engineering and Product Development (CEiiA), Collaborative Laboratory (CoLAB) National Institute for Space Research (INPE), Space Mechanics and Control Division (DMC) São Paulo State University (UNESP), Campus Guaratinguetá (FEG) Federal University of ABC (UFABC), Engineering, Modeling and Applied Social Sciences Center (CECS) |
Assunto:: | Filtro de partículas Satélites artificiais Programa de Satélites Sino-brasileiros de Recursos Terrestres (CBERS) Sensoriamento remoto |
Issue Date: | 16-Aug-2023 |
Publisher: | MDPI |
Citation: | SILVA, William Reis et al. The extended H∞ particle filter for attitude estimation applied to remote sensing satellite CBERS-4. Remote Sensing, [S.l.], v. 15, n. 16, 16 ago. 2023. DOI: https://doi.org/10.3390/rs15164052. Disponível em: https://www.mdpi.com/2072-4292/15/16/4052. Acesso em: 27 março 2024. |
Abstract: | An extension of the linear H∞ filter, presented here as the extended H∞ particle filter (EH∞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 H∞ 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 H∞ particle filter (EH∞PF) the nature of the system, composed of dynamics and noises, seeks to degrade the state estimate. The EH∞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 EH∞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. |
metadata.dc.description.unidade: | Faculdade UnB Gama (FGA) Curso de Engenharia Aeroespacial (FGA-Engenharia Aeroespacial) |
Licença:: | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). |
DOI: | https://doi.org/10.3390/rs15164052 |
Appears in Collections: | Artigos publicados em periódicos e afins |
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