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Three-Axis Attitude Estimation Using Rate-Integrating Gyroscopes
Author(s) -
John L. Crassidis,
F. Landis Markley
Publication year - 2016
Publication title -
journal of guidance control and dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.573
H-Index - 143
eISSN - 1533-3884
pISSN - 0731-5090
DOI - 10.2514/1.g000336
Subject(s) - gyroscope , kalman filter , inertial measurement unit , control theory (sociology) , attitude and heading reference system , attitude control , inertial navigation system , extended kalman filter , computer science , angular velocity , rate integrating gyroscope , rate gyro , inertial frame of reference , physics , artificial intelligence , engineering , vibrating structure gyroscope , control engineering , aerospace engineering , control (management) , quantum mechanics
Traditionally, attitude estimation has been performed using a combination of external attitude sensors and internal three-axis gyroscopes. There are many studies of three-axis attitude estimation using gyroscopes that read angular rates. Rate-integrating gyroscopes measure integrated rates or angular displacements, but three-axis attitude estimation using these types of gyroscopes has not been as fully investigated. This paper derives a Kalman filtering framework for attitude estimation using attitude sensors coupled with rate-integrating gyroscopes. To account for correlations introduced by using these gyroscopes, the state vector must be augmented, compared with filters using traditional gyroscopes that read angular rates. Two filters are derived in this paper. The first uses an augmented state-vector form that estimates attitude, gyroscope biases, and gyroscope angular displacements. The second ignores correlations, leading to a filter that estimates attitude and gyroscope biases only. Simulation compa...

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