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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 |
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container_title | Aerospace science and technology |
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creator | Xiong, K. Liu, L.D. Zhang, H.Y. |
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 |
format | article |
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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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