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Modified unscented Kalman filtering and its application in autonomous satellite navigation

In this paper, a modified unscented Kalman filter (UKF) for nonlinear stochastic systems is proposed, and it is applied to autonomous orbit determination for Earth satellites. Based on some standard results about the boundedness of stochastic processes and a new formulation of the unscented transfor...

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Published in:Aerospace science and technology 2009-06, Vol.13 (4), p.238-246
Main Authors: Xiong, K., Liu, L.D., Zhang, H.Y.
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Language:English
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description In this paper, a modified unscented Kalman filter (UKF) for nonlinear stochastic systems is proposed, and it is applied to autonomous orbit determination for Earth satellites. Based on some standard results about the boundedness of stochastic processes and a new formulation of the unscented transformation (UT), it is demonstrated that the design of the noise covariance matrix plays an important role in enhancing the filter stability. Furthermore, a particular design of the noise covariance matrix is proposed as a modification of the UKF. The modified UKF is less sensitive to the initial error than the usual one. High performance of the modified UKF is illustrated in comparison with the usual one by using the real data obtained from an Earth sensor.
doi_str_mv 10.1016/j.ast.2009.04.001
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subjects Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Navigation
Orbit determination
Physics
Satellites
Solid dynamics (ballistics, collision, multibody system, stabilization...)
Solid mechanics
Stability
Unscented Kalman filter
title Modified unscented Kalman filtering and its application in autonomous satellite navigation
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