@Article{SilvaHemeLeit:2017:EsAl,
author = "Silva, Felipe O. and Hemerly, Elder M. and Leite Filho, Waldemar
de Castro",
affiliation = "{Universidade Federal de Lavras (UFLA)} and {Instituto
Tecnol{\'o}gico de Aeron{\'a}utica (ITA)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "On the error state selection for stationary SINS alignment and
calibration Kalman filters – part I: Estimation algorithms",
journal = "Aerospace Science and Technology",
year = "2017",
volume = "61",
pages = "45--56",
month = "Feb.",
keywords = "Alignment, Calibration, Error state selection, Estimation, SINS.",
abstract = "This paper presents the first part of a study aiming at error
state selection in Kalman filters applied to the stationary
self-alignment and calibration (SSAC) problem of strapdown
inertial navigation systems (SINS). Estimation algorithms are
derived through the analytical manipulation of the full SINS error
model, thereby enabling us to investigate the dynamic coupling
existing between the state variables. As contributions of this
work, we demonstrate that the vertical velocity error is very
important for the estimation of almost all error states. Latitude
and altitude errors, in turn, are shown to uniquely affect the
inertial sensor bias estimates. Besides, the longitude error is
found to be totally detached from the system. As straightforward
consequence, Bar-Itzhack and Berman's error model turns out to be
inadequate for real implementations, and a 12-state Kalman filter
is shown to be the optimal error state selection for SSAC
purposes. Simulated and experimental tests confirm the adequacy of
the outlined conclusions.",
doi = "10.1016/j.ast.2016.11.019",
url = "http://dx.doi.org/10.1016/j.ast.2016.11.019",
issn = "1270-9638",
language = "en",
targetfile = "silva_error.pdf",
urlaccessdate = "27 abr. 2024"
}