@InProceedings{SilvaKugaZana:2014:ExHiFi,
author = "Silva, William Reis and Kuga, H{\'e}lio Koiti and Zanardi, Maria
Cecilia Fran{\c{c}}a de Paula Santos",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal
do ABC (UFABC)}",
title = "The extended H-infinite filter for calibration and attitude
determination using real data of CBERS-2 satellite",
booktitle = "Proceedings...",
year = "2014",
pages = "1--18",
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 = "extended H-infinite filter, second order extended H-infinite
filter, attitude estimation, gyros drift.",
abstract = "This work describes the attitude and the gyros drift estimation
for real satellite CBERS-2 (China Brazil Earth Resources Satellite
2) using the Second-Order Extended H\∞ Filter for nonlinear
systems. The attitude dynamical model is described by nonlinear
equations involving the Euler angles. The attitude sensors
available are two DSS (Digital Sun Sensors), two IRES (Infra-Red
Earth Sensor), and one triad of mechanical gyros. The two IRES
give direct measurements of roll and pitch angles with a certain
level of error. The two DSS are mounted on the satellite body such
that they are nonlinear functions of roll, pitch, and yaw attitude
angles. Herein one proposes to use an extension of the H\∞
linear filter for the nonlinear case of attitude estimation with
nonlinearity in both the dynamics and the measurement model. The
aim is to highlight and magnify the properties of the H\∞
filter in terms of its favourable characteristics. The results in
this work show that one can reach accuracies in attitude
determination within the prescribed requirements, besides
providing estimates of the gyro drifts which can be further used
to enhance the gyro error model and that the Second-Order Extended
H\∞ Filter is more robust than Extended Kalman Filter.",
conference-location = "Laurel",
conference-year = "2014",
label = "lattes: 1786255724025154 2 SilvaKugaZana:2014:EXHIFI",
language = "en",
url = "https://dnnpro.outer.jhuapl.edu/Portals/35/ISSFD24_Paper_Release/ISSFD24_Paper_S4-4_Silva.pdf",
urlaccessdate = "03 jun. 2024"
}