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.

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