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UKF based on-orbit gyro and magnetometer bias estimation as a part of the attitude determination procedure for a small satellite
Date
2011-12-01
Author
Söken, Halil Ersin
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In this study an unscented Kalman filter (UKF) based magnetometer and gyro bias estimation algorithm is presented as a part of the attitude determination procedure for a small satellite, which has three magnetometers and three gyros as measurement sensors. Differently from the existing studies both magnetometer and gyro biases are estimated as well as the attitude parameters. Kinematics of the satellite is modeled via using quaternion parameterization. In order to enable estimation of all parameters simultaneously without a high computational cost, two methods known in advance are used. First, quaternion based modeling constraint that is met because of the unit norm of quaternion is overrun by enforcing constraint as a dummy measurement through the measurement model, instead of employing three-element error quaternion state as attitude representation. Second, in filter formulations gyro-based model is used for attitude propagation. Validity of the proposed method is confirmed by simulations. © 2011 ICROS.
URI
https://hdl.handle.net/11511/69771
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Department of Aerospace Engineering, Conference / Seminar
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Reconfigurable UKF for in-flight magnetometer calibration and attitude parameter estimation
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In this study a reconfigurable unscented Kalman filter (UKF) based algorithm for the estimation of magnetometer biases and scale factors is proposed as a part of the attitude estimation scheme of a pico satellite. Algorithm is composed of two stages; in first stage UKF estimates magnetometer biases and scale factors as well as six attitude parameters of the satellite. Differently from the existing algorithms, scale factors are not treated together with the other parameters as a part of the state vector; thr...
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H. E. Söken, “UKF based on-orbit gyro and magnetometer bias estimation as a part of the attitude determination procedure for a small satellite,” 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69771.
