International Journal of Computer Network and Information Security (IJCNIS)
IJCNIS Vol. 3, No. 4, 8 Jun. 2011
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Satellite Attitude Determination Filter using Square Root based Spherical Simplex Unscented Transformation
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Author(s)
Kaichun Zhao
1,*
Zheng You
2
Index Terms
Spheral simplex unscented transformation, quare root, scented Kalman filter, titude measurement, herical simplex
Abstract
A square root based spherical simplex unscented transform was adopted in micro satellite attitude determination filter. The filter computation cost was reduced evidently by means of spherical simplex unscented transformation (SSUT) and the square root technique with modified Rodrigues parameters (MRPs). The filter performance and numerical stability were guaranteed by unscented transformation with positive-semi definiteness of the state covariance propagation. The simulation results of some micro-satellite showed that this algorithm could insure accuracy, fast convergence and high robustness with high computation efficiency, which was suitable for the attitude estimation of micro-satellite.
Cite This Paper
Kaichun Zhao, Zheng You, "Satellite Attitude Determination Filter using Square Root based Spherical Simplex Unscented Transformation", International Journal of Computer Network and Information Security(IJCNIS), vol.3, no.4, pp.32-38, 2011. DOI:10.5815/ijcnis.2011.04.05
Reference
[1]E. J. Lefferts, F. L. Markley, M. D. Shuster, Kalman Filtering for Spacecraft Attitude Estimation, Journal of. Guidance, Control and Dynamics,1982,5(5):417-429.
[2]S. J. Julier and J. K. Uhlmann, “Unscented filtering and nonlinear estimation,” Proc. IEEE, vol. 92, pp. 401–422, Mar. 2004.
[3]R. van der Merwe and E. A. Wan, “Sigma-point Kalman filters for nonlinear estimation and sensor-fusion-applications to integrated navigation”, AIAA Guidance, Navigation, and Control Conference, v3, p 1735-1764, 2004.
[4]S. J. Julier and J. K. Uhlmann, and H. Durrant-Whyte, “A new approach for filtering nonlinear systems,” Proceedings of the American Control Conference, pp. 1628–1632, 1995.
[5]Julier S J, Uhlmann J K, Durrant-Whytte H F. A new method for the nonlinear transformation of means and covariance in filter and estimators. IEEE Transactions on automatic control, 2000,45(3):477-482.
[6]Merwe R V, Doucet A, Freitas N De. The Unscented Particle Filter. Technical Report CUED/F-INPENG/TR 380, Cambridge University Engineering Department,2000
[7]Julier S J, Uhlmann J K. Reduced sigma point filters for the propagation of means and covariances though nonlinear transformations. Proceeding of the American Control Conference.Anchorage AK,2002.
[8]Julier S J. The spherical simplex unscented transformation[A]. Proceeding of the American Control Conference.Denver, Colorado,2003.
[9]Chunshi Fan, Zheng You.Highly Efficient Sigma Point Filter for Spacecraft Attitude and Rate Estimation. Mathematical Problems in Engineering.Volume 2009 (2009), Article ID 507370, 23 pages.
[10]J. Levesque, “Second-Order Simplex Sigma Points for Nonlinear Estimation”, AIAA Guidance, Navigation and Control Conference and Exhibit.2006.
[11]R. van der Merwe, E.A. Wan, Square-root unscented Kalman filter for state and parameter estimation, in: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Proces- sing, Salt Lake City, UT, May 2001, 3461–3464.
[12]Xiaojun Tang, JieYan, DuduZhong. Square-root sigma-point Kalman filtering for spacecraft relative navigation. Acta Astronautica 66 (2010) 704-713.
[13]Shuster, M.D., ” A survey of attitude representations”. Journal of the Astronautical Sciences, 41(4), 439-517(1993).
[14]Crassidis, J.L., ”Sigma-point Kalman filtering for Integrated GPS and Inertial Navigation”, IEEE Transactions on Aerospace and Electronic Systems, 42(2), 750-756(2006).