@InProceedings{SilveiraKugaOliv:2013:ApExKa,
               author = "Silveira, guilherme da and Kuga, Helio Koiti and Oliveira, 
                         {\'E}lcio Jeronimo de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and IAE – Instituto de 
                         Aeron{\'a}utica e Espa{\c{c}}o Pra{\c{c}}a Mal. Eduardo Gomes, 
                         50 12228904 – S{\~a}o Jos{\'e} dos Campos, SP – BRAZIL",
                title = "Application of extended Kalman filter in estimation of reentry 
                         trajectories",
            booktitle = "Proceedings...",
                 year = "2013",
                pages = "3618--3627",
         organization = "International Congress of Mechanical Engineering, 22. (COBEM).",
            publisher = "ABCM",
                 note = "{Setores de Atividade: Pesquisa e desenvolvimento 
                         cient{\'{\i}}fico.}",
             keywords = "Extended Kalman filter, reentry trajectories, estimation.",
             abstract = "Atmospheric reentry dynamics of space vehicles represents a 
                         complex phenomenon for which a mathematical model is difficult to 
                         obtain, partly because of the uncertainty related to the 
                         aerodynamic efforts acting on the vehicle during reentry. The use 
                         of estimation techniques to determine the unknown parameters of 
                         the vehicle dynamics can help to enlighten this phenomenon. This 
                         work presents the data processing of the atmospheric reentry of 
                         the platform Plataforma SubOrbital (PSO1), a microgravity platform 
                         launched from the Centro de Lan{\c{c}}amento da Barreira do 
                         Inferno (CLBI), in Natal, Brazil, in 2000. Using actual flight 
                         position data, relative to CLBIs radar, and applying an Extended 
                         Kalman Filter methodology, the variables that describe the dynamic 
                         behavior of the platform are estimated. The mathematical model of 
                         the platform during reentry is composed of five state variables: 
                         two positions, two velocities and one aerodynamic parameter. The 
                         aerodynamic efforts acting on the platform depend to great extent 
                         on such parameter. Results have shown correct position estimation, 
                         reflected in low filter residues, and consistent velocity 
                         estimation. The aerodynamic parameter grows after the platform 
                         reenters the atmosphere, and its value depends on the dynamic 
                         noise level associated with the dynamic model. The values of the 
                         standard deviation associated with the state vector are considered 
                         in both the filter tuning and convergence analysis, showing 
                         consistency of the aerodynamic characteristics.",
  conference-location = "Ribeirao Preto",
      conference-year = "3-7 Nov.2013",
                 issn = "2176-5480",
                label = "lattes: 1786255724025154 2 SilveiraKugaOliv:2013:ApExKa",
             language = "en",
           targetfile = "755silkuga.pdf",
        urlaccessdate = "20 maio 2024"
}