Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-26T02:07:45.316Z Has data issue: false hasContentIssue false
  • English
  • Français

Gyro-stellar inertial attitude estimation for satellite with high motion rate

Published online by Cambridge University Press:  18 April 2022

C.-L. Lin Open the ORCID record for C.-L. Lin [Opens in a new window] ,
J.-C. Li ,
C.-L. Chiu ,
Y.-W.A. Wu  and
Y.-W. Jan
C.-L. Lin*
Affiliation:
Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan
J.-C. Li
Affiliation:
Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan National Space Organization, Hsinchu, Taiwan
C.-L. Chiu
Affiliation:
National Space Organization, Hsinchu, Taiwan
Y.-W.A. Wu
Affiliation:
National Space Organization, Hsinchu, Taiwan
Y.-W. Jan
Affiliation:
National Space Organization, Hsinchu, Taiwan
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

For a common micro-satellite, orbiting in a circular sun-synchronous orbit (SSO) at an altitude between 500 and 600km, the satellite attitude during off-nadir imaging and staring-imaging operations can be up to ±45 degree on roll and pitch angles. During these off-nadir pointing for both multi-trip operation and staring imaging operations, the spacecraft body is commonly subject to high-rate motion. This posts challenges for a spacecraft attitude determination subsystem called Gyro Stellar Inertial Attitude Estimate (GS IAE), which employs gyros and star sensors to maintain the required attitude knowledge, since star trackers will severely degrade attitude estimation accuracies when the spacecraft is subject to high-rate motion. This paper analyses the star motion-induced errors for a typical star tracker, models the star motion-induced errors to assess the performance impact on the attitude estimation accuracy, and investigates the adaptive extended Kalman filter design in the GS IAE while evaluating its effectiveness.

Keywords

Attitude estimation and controlKalman filterLow earth orbit satelliteStellar sensing
Type
Research Article
Information
The Aeronautical Journal , Volume 126 , Issue 1306 , December 2022 , pp. 1967 - 1981
Check for updates
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Lefferts, E.J., Markley, F.L. and Shuster, M.D. Kalman filtering for spacecraft attitude estimation, AIAA J. Guidance Control Dyn., 1982, 5, (5), pp 417–429.10.2514/3.56190CrossRefGoogle Scholar
Wei, W.T., Tsai, Y.F., Yeh, M., Jan, Y.W. and Wu, Y.W. MEMS-based gyro-stellar inertial attitude estimate for NSPO micro-sat program, Proceedings of IEEE Aerospace Conference, 2019, pp 1–15.10.1109/AERO.2019.8742107Google Scholar
Hou, B., He, Z., Zhou, H. and Wang, J. Integrated design and accuracy analysis of star sensor and gyro on the same benchmark for satellite attitude determination system, IEEE/CAA J. Automatica Sinica, 2019, 6, (4), pp 1074–1080.10.1109/JAS.2019.1911600CrossRefGoogle Scholar
Wu, Y.A. and Hein, D.H. Stellar inertial attitude determination for LEO spacecraft, Proceedings of IEEE Conference on Decision and Control, 1996, 3, pp 3236–3244.Google Scholar
Choi, S.H. and Park, C.G. Attitude determination and disturbance estimation based on adaptive Kalman filter for nano-satellite, Proceedings of International Conference on Control, Automation and Systems, 2016, pp 1020–1024.10.1109/ICCAS.2016.7832434Google Scholar
Kim, A. and Golnaraghi, M.F. A quaternion-based orientation estimation algorithm using an inertial measurement unit, Position Location and Navigation Symposium, 2004, pp 268–272.Google Scholar
Kraft, E. A quaternion-based unscented Kalman filter for orientation tracking, Proceedings of International Conference of Information Fusion, 2003, pp 47–54.10.1109/ICIF.2003.177425Google Scholar
LaViola, J.J. A comparison of unscented and extended Kalman filtering for estimating quaternion motion, Proceedings of the American Control Conference, 2003, pp 2435–2440.Google Scholar
Feng, B., Fu, M., Ma, H., Xia, Y. and Wang, B. Kalman filter with recursive covariance estimation—sequentially estimating process noise covariance, IEEE Trans. Ind. Electron., 2014, 61, (11), pp 6253–6263.10.1109/TIE.2014.2301756CrossRefGoogle Scholar
Huang, Y., Zhang, Y., Wu, Z., Li, N. and Chambers, J. A novel adaptive Kalman filter with inaccurate process and measurement noise covariance matrices, IEEE Trans. Autom. Control, 2018, 63, (2), pp 594–601.10.1109/TAC.2017.2730480CrossRefGoogle Scholar
Crassidis, J.L., Cheng, Y., Fosbury, A.M. and Nebelecky, C.K. Decentralised attitude estimation using a quaternion covariance intersection approach, J. Astronaut. Sci., 2013, doi: 10.1007/BF03321497.Google Scholar
Dey, A., Sadhu, S. and Ghoshal, T.K. Adaptive divided difference filter for nonlinear systems with unknown noise, Proceedings of The International Conference on Control, Instrumentation, Energy and Communication, 2014, pp 573–577.10.1109/CIEC.2014.6959154CrossRefGoogle Scholar
Patra, N. and Sadhu, S. Adaptive extended Kalman filter for the state estimation of anti-lock braking system, Proceedings of Annual IEEE India Conference, 2015, pp 1–6.10.1109/INDICON.2015.7443199Google Scholar
Dong, Y. and Colibrys, S.A. EMS inertial navigation systems for aircraft, 2013, doi: 10.1533/9780857096487.2.177.Google Scholar
ST-16RT2 Star Tracker. Sinclair Interplanetary. https://satsearch.co/products/sinclair-interplanetary-second-generation-star- tracker-st-16rt2.Google Scholar