@InProceedings{GarciaKugaZanaMato:2014:AtEsPr,
               author = "Garcia, Roberta Veloso and Kuga, H{\'e}lio Koiti and Zanardi, 
                         Maria Cecilia Fran{\c{c}}a de Paula Santos and Matos, Nicholas de 
                         Freitas Oliveira",
          affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Universidade Federal do ABC 
                         (UFABC)} and {Universidade Estadual Paulista (UNESP)}",
                title = "Attitude estimation process of the sensing remote satellite 
                         cbers-2 with unscented kalman filter and quaternion incremental, 
                         using real data",
            booktitle = "Proceedings...",
                 year = "2014",
                pages = "1--15",
         organization = "International Symposium on Space Flight Dynamics, 24. (ISSFD).",
            publisher = "Johns Hopkins - Applied Physics Laboratory",
                 note = "{Setores de Atividade: Pesquisa e desenvolvimento 
                         cient{\'{\i}}fico.}",
             keywords = "Unscented Kalman filter, attitude estimation, quaternions, 
                         extended Kalman filter.",
             abstract = "This work is related to the dynamics of rotational motion of 
                         artificial satellites, that is, its orientation (attitude) with 
                         respect to an inertial reference system. The attitude 
                         determination process, in general, involves the knowledge of 
                         nonlinear estimation techniques and is essential to the safety and 
                         control of the satellite and payload. The aim of this work is to 
                         study the influence of real data of the CBERS-2 (China Brazil 
                         Earth Resources Satellite) satellite in the attitude estimation 
                         process when the estimator is the Unscented Kalman Filter (UKF) 
                         and the attitude is represented by quaternion incremental. The 
                         attitude sensors available are DSS (Digital Sun Sensor), IRES 
                         (Infrared Earth Sensor), and the gyros. For nonlinear systems, the 
                         UKF uses a carefully selected set of sample points to map the 
                         probability distribution more accurately than the linearization of 
                         the standard Extended Kalman Filter (EKF). Herein the proposal is 
                         to estimate the attitude and the drift of the gyros obtained by 
                         the UKF and EKF with quaternion incremental and compare them. The 
                         results show that, although the EKF and UKF have roughly the same 
                         accuracy, the UKF leads to a convergence of the state vector 
                         faster than the EKF. This fact was expected, since the UKF 
                         prevents the linearizations needed for EKF, when the system has 
                         some nonlinearity in their equations.",
  conference-location = "Laurel",
      conference-year = "2014",
                label = "lattes: 1786255724025154 2 GarciaKugaZanaMato:2014:ATESPR",
             language = "en",
                  url = "https://dnnpro.outer.jhuapl.edu/Portals/35/ISSFD24_Paper_Release/ISSFD24_Paper_S4-3_VelosoGarcia.doc",
        urlaccessdate = "26 abr. 2024"
}