Adaptive Tuning of the Unscented Kalman Filter for Satellite Attitude Estimation
Publication: Journal of Aerospace Engineering
Volume 28, Issue 3
Abstract
Determining the process noise covariance of the unscented Kalman filter (UKF) is a difficult procedure. The analytical approximation method gives satisfactory results in certain cases, but it fails when generalized for the estimation of the extended states, such as the case that sensor biases or scale factors are included in the state vector. The main aim of this research is to find an appropriate tuning algorithm for the process noise covariance of the UKF when the magnetometer biases are estimated, as well as attitude and gyro biases. In this sense, an adaptive tuning method for an UKF that is used for satellite attitude estimation is given and the adaptive UKF algorithm is tested in various scenarios for the attitude and sensor bias estimation. The given adaptation method is an easy way of tuning the filter, especially in the absence of any analytical approximation for the calculation of the process noise covariance, and the performed simulations show that by using the adaptive UKF, it is possible to get accurate estimates that are close to optimal.
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Acknowledgments
This work was supported in part by the Japanese government with the MONBUKAGAKUSHO scholarship, and also by the Japan Aerospace Exploration Agency (JAXA) with a research grant.
References
Busse, F. D., How, J. P., and Simpson, J. (2003). “Demonstration of adaptive extended Kalman filter for low earth orbit formation estimation using CDGPS.” J. Inst. Navig., 50(2), 79–93.
Crassidis, J. L., and Markley, F. L. (2003). “Unscented filtering for spacecraft attitude estimation.” J. Guid. Contr.Dyn., 26(4), 536–542.
Dunik, J., Simandl, M., and Straka, O. (2009). “Methods for estimating state and measurement noise covariance matrices: Aspects and comparison.” Proc., 15th IFAC Symp. System Identification, IFAC Publications, Oxford, U.K., 972–977.
Farrenkopf, R. L. (1978). “Analytic steady-state accuracy solutions for two-common spacecraft attitude estimators.” J. Guid. Contr.Dyn., 1(4), 282–284.
Fosbury, A. M. (2011). “Steady-state accuracy solutions of more spacecraft attitude estimators.” Proc., AIAA Guidance, Navigation and Control Conf., AIAA, Reston, VA.
Inamori, T., Nakasuka, S., and Sako, N. (2009). “In-orbit magnetic disturbance estimation and compensation using UKF in nano-satellite mission.” Proc., AIAA Guidance, Navigation and Control Conf., AIAA, Reston, VA.
Julier, S., Uhlmann, J., and Durrant-Whyte, H. F. (1996). “A general method for approximating nonlinear transformations of probability distributions.” 〈http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.46.6718〉 (May 18, 2010).
Julier, S., Uhlmann, J., and Durrant-Whyte, H. F. (2000). “A new method for the nonlinear transformation of means and covariances in filters and estimators.” IEEE Trans. Autom. Control, 45(3), 477–482.
Julier, S. J., Uhlmann, J. K., and Durrant-Whyte, H. F. (1995). “A new approach for filtering nonlinear systems.” Proc., American Control Conf., 3, American Automatic Control Council, New York, 1628–1632.
Lee, D. J., and Alfriend, K. T. (2004). “Adaptive sigma point filtering for state and parameter estimation.” Proc., AIAA/AAS Astrodynamics Specialist Conf. Exhibit, AIAA, Reston, VA.
Markley, F. L., and Reynolds, R. G. (2000).“Analytic steady-state accuracy of a spacecraft attitude estimator.” J. Guid. Contr.Dyn., 23(6), 1065–1067.
Maybeck, P. S. (1982). Stochastic models, estimation, and control, Vol. 2, Academic Press, New York.
Mohamed, A. H., and Schwarz, K. P. (1999). “Adaptive Kalman filtering for INS/GPS.” J. Geodes, 73(4), 193–203.
Sekhavat, P., Gong, Q., and Ross, I. M. (2007). “NPSAT1 parameter estimation using unscented Kalman filter.” Proc., 2007 American Control Conf., IEEE, Piscataway, NJ, 4445–4451.
Soken, H. E., and Hajiyev, C. (2012). “UKF-based reconfigurable attitude parameter estimation and magnetometer calibration.” IEEE Trans. Aero.Electron. Syst., 48(3), 2614–2627.
Vinther, K., Jensen, K. F., Larsen, J. A., and Wisniewski, R. (2011). “Inexpensive CubeSat attitude estimation using quaternions and unscented Kalman filtering.” Autom. Cont. Aerosp., 4(1).
Wertz, J. R. (1988). Spacecraft attitude determination and control, Kluwer Academic Publishers, Dordrecht, the Netherlands.
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© 2014 American Society of Civil Engineers.
History
Received: Dec 17, 2012
Accepted: Feb 5, 2014
Published online: Feb 7, 2014
Discussion open until: Dec 22, 2014
Published in print: May 1, 2015
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