Fault Tolerant Attitude Estimation for a Nanosatellite Using Adaptive Kalman Filter with Single Scaling Factor

Authors

  • Hasan Kınataş MSc. student at Aeronautics and Astronautics Faculty, Istanbul Technical University, Istanbul
  • Cengiz Hacızade Prof. Dr.

Keywords:

Nanosatellite, attitude estimation, adaptive Kalman filtering, fault, magnetometer, sun sensor

Abstract

In this study an integrated adaptive TRIAD/Extended Kalman Filter (EKF) attitude estimation algorithm is presented, in which the TRIAD and an adaptive EKF are combined to estimate the attitude of a nanosatellite. The quaternion set produced by the TRIAD is provided as input to the adaptive EKF. Adaptive EKF estimates the final quaternion set and using a Single Scaling Factor (SSF), it readjusts the measurement noise covariance matrix in case of a sensor fault. The performance of the presented algorithm is tested against two different fault types as noise increment and continuous bias in attitude sensors. As a result of simulations, it is seen that although the performance of the conventional EKF reduces significantly in case of sensor faults, adaptive EKF continues to give reliable attitude estimations.

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Author Biography

Cengiz Hacızade, Prof. Dr.

Prof. Dr. at Aeronautics and Astronautics Faculty, Istanbul Technical University, Istanbul, Turkey

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Published

29-07-2022

How to Cite

[1]
H. Kınataş and C. Hacızade, “Fault Tolerant Attitude Estimation for a Nanosatellite Using Adaptive Kalman Filter with Single Scaling Factor”, JAST, vol. 15, no. 2, pp. 74–93, Jul. 2022.

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Articles