@Article{GarciaKugaSilvZana:2018:UnKaFi,
author = "Garcia, Roberta Veloso and Kuga, H{\'e}lio Koiti and Silva,
William Reis and Zanardi, Maria Cecilia",
affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Unscented Kalman filter and smoothing applied to attitude
estimation of artificial satellites",
journal = "Computational and Applied Mathematics",
year = "2018",
volume = "2018",
keywords = "Rauch–Tung–Striebel smoother · Unscented Kalman filter · Attitude
estimation · Euler angles.",
abstract = "This article uses the state smoothing methodology applied to
nonlinear systems to refine the attitude of artificial satellites.
In this paper, simulated data of telemetry and ephemeris of a
satellite with the specifications of China Brazil Earth Resources
Satellite are considered and the dynamic system is described by
the set of kinematic equations in terms of the Euler angles and
the bias vector of gyroscope. The estimator used to determine the
forward estimates in time is the Unscented Kalman filter, while
the RauchTungStriebel fixed interval estimator makes the estimate
backward time. The results show that, although the time of the
estimation process is slightly increased, the smoother presents
estimated attitude and bias closer to the real values than the
estimated values when using only the Unscented Kalman filter.
Therefore, the smoother can be considered as a technique that
provides refined measurements of the attitude and bias of the
gyroscope that may serve to calibrate the Kalman filter for next
estimates.",
doi = "10.1007/s40314-018-0576-8",
url = "http://dx.doi.org/10.1007/s40314-018-0576-8",
issn = "2238-3603",
language = "en",
targetfile = "garcia_unscented.pdf",
urlaccessdate = "27 abr. 2024"
}