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A unity-norm preserving quaternion extended Kalman filter

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dc.contributor.author Hashlamon, Iyad
dc.date.accessioned 2020-12-14T08:24:18Z
dc.date.accessioned 2022-05-22T08:53:07Z
dc.date.available 2020-12-14T08:24:18Z
dc.date.available 2022-05-22T08:53:07Z
dc.date.issued 2020-10
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/8150
dc.description.abstract Preserving the quaternion unity norm has significant importance when combined with the extended Kalman filter (EKF) for state estimation of nonlinear systems perturbed by noise using noisy measurements. Although this unity challenge is solved numerically on the estimated quaternion, it is normalized out of the EKF algorithm. Projecting this constraint on the derivation of the EKF algorithm to preserve the quaternion unity norm is the purpose of this paper. The quaternion unity norm constraint is derived in two forms and projected on the EKF gain derivation. Then this gain is used to update the quaternion vector keeping its unity norm. The results show that the unity norm is preserved using the proposed constrained quaternion EKF (CQEKF) even though sudden changes occur. en_US
dc.language.iso en en_US
dc.publisher International Conference on Applied Science and Technology (ICAST) en_US
dc.subject Extended Kalman filter en_US
dc.subject quaternion en_US
dc.subject robots en_US
dc.title A unity-norm preserving quaternion extended Kalman filter en_US
dc.type Article en_US

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