@Article{SilvaGaPaKuZaBa:2023:ExH&Pa,
               author = "Silva, William Reis and Garcia, Roberta Veloso and Pardal, Paula 
                         C. P. M. and Kuga, Helio Koiti and Zanardi, Maria Cec{\'{\i}}lia 
                         F. P. S. and Baroni, Leandro",
          affiliation = "{Universidade de Bras{\'{\i}}lia (UnB)} and {Universidade de 
                         S{\~a}o Paulo (USP)} and {Center of Engineering and Product 
                         Development (CEiiA)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade Estadual Paulista (UNESP)} and 
                         {Universidade Federal do ABC (UFABC)}",
                title = "The Extended H\∞ Particle Filter for Attitude Estimation 
                         Applied to Remote Sensing Satellite CBERS-4",
              journal = "Remote Sensing",
                 year = "2023",
               volume = "15",
               number = "16",
                pages = "e4052",
                month = "Aug.",
             keywords = "attitude estimation, China–Brazil Earth Resources Satellite, 
                         extended H\∞,,, particle filter, nonlinear state estimation, 
                         particle filter.",
             abstract = "An 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 (ChinaBrazil 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.",
                  doi = "10.3390/rs15164052",
                  url = "http://dx.doi.org/10.3390/rs15164052",
                 issn = "2072-4292",
                label = "self-archiving-INPE-MCTIC-GOV-BR",
             language = "en",
           targetfile = "remotesensing-15-04052-v2.pdf",
        urlaccessdate = "05 maio 2024"
}