@Article{GarciaKugaZana:2016:UnKaFi,
author = "Garcia, Roberta Veloso and Kuga, Helio Koiti and Zanardi, Maria
Cec{\'{\i}}lia F. P. S.",
affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Universidade Federal do ABC
(UFABC)}",
title = "Unscented Kalman filter for determination of spacecraft attitude
using different attitude parameterizations and real data",
journal = "Journal of Aerospace Technology and Management",
year = "2016",
volume = "8",
number = "1",
pages = "82--90",
month = "jan./mar.",
keywords = "Attitude estimation, Real data, Unscented Kalman Filter, Extended
Kalman Filter, Quaternion, Euler angles.",
abstract = "The non-linear estimators are certainly the most important
algorithms applied to real problems, especially those involving
the attitude estimation of spacecraft. The purpose of this paper
was to use real data of sensors to analyze the behavior of
Unscented Kalman Filter (UKF) in attitude estimation problems when
it is represented in different ways and compare it with the
standard estimator for non-linear estimation problems. The
robustness of the estimation was performed when this was subjected
to imprecise initial conditions. The attitude parametrization was
described in Euler angles, quaternion and quaternion incremental.
The satellite China-Brazil Earth Resources Satellite and
measurements provided by the Satellite Control Center of the
Instituto Nacional de Pesquisas Espaciais were considered in the
study. The results indicate that the behaviors for both estimators
were equivalent for such parameterizations under the same
conditions. However, comparing the Unscented Kalman Filter with
the standard filter for non-linear systems, Extended Kalman Filter
(EKF), it was observed that, in the presence of inaccurate initial
conditions, the Unscented Kalman Filter presented a fast
convergence whereas Extended Kalman Filter had problems and only
converged later on.",
doi = "10.5028/jatm.v8i1.509",
url = "http://dx.doi.org/10.5028/jatm.v8i1.509",
issn = "1984-9648",
label = "self-archiving-INPE-MCTI-GOV-BR",
language = "en",
targetfile = "garcia_unscented.pdf",
urlaccessdate = "27 abr. 2024"
}