Extended Kalman Filtering Using Quaternion Normalization for Attitude Measurement While Drilling

Extended Kalman filtering (EKF) has extensively applied in attitude measurement while drilling, in which quaternion is commonly used as the state vector. However, for the dynamic model, the quaternion usually does not meet the requirement of the unit norm as time goes, which leads to the invalidity of attitude calculation. For this, this paper studies the EKF algorithm using normalized quaternion for attitude measurement while drilling. It establishes the state and measurement equations using quaternion according to specific rotation model of the drilling tool. Then, normalization is applied in each estimation step. Illustrative examples show the performance superiority of the method considered, compared with the method free of quaternion normalization and static calculation method.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/icmsp64464.2024.10866762
Primary Topic
Inertial Sensor and Navigation
Type
article
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article

Extended Kalman Filtering Using Quaternion Normalization for Attitude Measurement While Drilling

Tao Jiang, Minghao Gao, Guangxiao Jian
Inertial Sensor and Navigation
article

Extended Kalman Filtering Using Quaternion Normalization for Attitude Measurement While Drilling

Tao Jiang, Minghao Gao, Guangxiao Jian
article en

Abstract

Extended Kalman filtering (EKF) has extensively applied in attitude measurement while drilling, in which quaternion is commonly used as the state vector. However, for the dynamic model, the quaternion usually does not meet the requirement of the unit norm as time goes, which leads to the invalidity of attitude calculation. For this, this paper studies the EKF algorithm using normalized quaternion for attitude measurement while drilling. It establishes the state and measurement equations using quaternion according to specific rotation model of the drilling tool. Then, normalization is applied in each estimation step. Illustrative examples show the performance superiority of the method considered, compared with the method free of quaternion normalization and static calculation method.

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