%0 Conference Proceedings
%4 sid.inpe.br/plutao/2013/12.12.15.12.42
%2 sid.inpe.br/plutao/2013/12.12.15.12.43
%@issn 2176-5480
%F lattes: 1786255724025154 2 SilveiraKugaOliv:2013:ApExKa
%T Application of extended Kalman filter in estimation of reentry trajectories
%D 2013
%A Silveira, guilherme da,
%A Kuga, Helio Koiti,
%A Oliveira, Élcio Jeronimo de,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation IAE – Instituto de Aeronáutica e Espaço Praça Mal. Eduardo Gomes, 50 12228904 – São José dos Campos, SP – BRAZIL
%@electronicmailaddress
%@electronicmailaddress helio.kuga@inpe.br
%B International Congress of Mechanical Engineering, 22 (COBEM).
%C Ribeirao Preto
%8 3-7 Nov.2013
%I ABCM
%P 3618-3627
%S Proceedings
%K Extended Kalman filter, reentry trajectories, estimation.
%X 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 Lançamento 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.
%@language en
%3 755silkuga.pdf
%O Setores de Atividade: Pesquisa e desenvolvimento científico.