DocumentCode :
3171572
Title :
Attitude estimation based on inertial and position measurements
Author :
Gros, Sebastien ; Diehl, Moritz
Author_Institution :
Optimization in Eng. Center (OPTEC), K.U. Leuven, Heverlee, Belgium
fYear :
2012
fDate :
10-13 Dec. 2012
Firstpage :
1758
Lastpage :
1763
Abstract :
Attitude estimation arises in many applications, and is crucial for the aerospace and aeronautic industry. A classical approach to perform the attitude estimation is via Inertial Measurement Unit (IMU) data and a set of measured observation vectors, both in the object and inertial reference frame. The attitude estimation can be then formulated as a constrained least-squares problem. As a possible alternative, attitude estimation can be performed using IMU data and a set of measured positions, hence removing the need for observation vectors. Attitude estimation based on IMU and position measurements is already undergoing industrial research. However, the underlying estimation problem does not necessarily admit a unique solution, and can therefore degenerate depending on the object trajectories. This paper theoretically investigates this approach to attitude estimation, and provides a simple, explicit relationship between the standard deviation of the attitude estimation and the object trajectories, which is independent of the choice of parametrization of the special orthogonal group SO(3).
Keywords :
attitude control; estimation theory; least mean squares methods; position measurement; vectors; IMU; aeronautic industry; aerospace industry; attitude estimation; constrained least-squares problem; inertial measurement; inertial measurement unit; object trajectories; observation vector; orthogonal group SO(3); position measurement; Estimation error; Position measurement; Sensitivity; Standards; Trajectory; Vectors; IMU and position measurements; SO(3) parametrization; attitude estimation; estimation accuracy; projected Hessian;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
ISSN :
0743-1546
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2012.6426420
Filename :
6426420
Link To Document :
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