By Topic

Inertial navigation attitude velocity and position algorithms using quaternion Scaled Unscented Kalman filtering

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Khoder, W. ; Lab. d''Analyse des Syst. du Littoral, Univ. du Littoral Cote d''Opale, Calais ; Fassinut-Mombot, B. ; Benjelloun, M.

In this paper, a scaled unscented Kalman filter (SUKF) based on the quaternion concept is designed for determination of the attitude, velocity and position parameters in inertial navigation system (INS) under large attitude error conditions. In this feedback filter, only bias effects are considered to be independent states and are used to compensate for navigation errors. To preserve the nonlinear nature of unit quaternion, the weighted mean computation for quaternions is derived in rotational space as a barycentric mean with renormalization and a multiplicative quaternion-error is used for predicted covariance computation of the quaternion because it represents the distance from the predicted mean quaternion. The updates are performed using quaternion multiplication which guarantees that quaternion normalization is maintained in the filter. Since the quaternion process noise increases the uncertainty in attitude orientation, modeling it as a vector part of quaternion is considered. Simulation and experimental results indicate a satisfactory performance of the newly developed model.

Published in:

Industrial Electronics, 2008. IECON 2008. 34th Annual Conference of IEEE

Date of Conference:

10-13 Nov. 2008