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38 results on '"Wang, Xiao-chu"'

4. Determination of vision-based relative state by modified unscented Kalman filter

Author

王晓初 Wang Xiao-chu, 尤政 You Zheng, and 赵开春 Zhao Kai-chun

Subjects
Engineering, Computer simulation, business.industry, Computation, Kinematics, Kalman filter, Covariance, Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials, Extended Kalman filter, Position (vector), Control theory, Unscented transform, business
Abstract

On the basis of the principle of a VISNAV sensor,this paper researches how to determine the vision-based relative state between two satellites with disturbances.By taking the VISNAV sensor as a relative state sensor,the problem mentioned above is solved by a modified Kalman filter algorithm.In consideration of the relative orbit dynamics equation with disturbance and the relative attitude kinematic equation,it gives modified discrete equation and a calculation method for the error covariance matrix.By which the method avoids the complicated real-time operations of large dimensional matrices in every loop and reduces computation amounts.Finally,the corresponding modified Unscented Kalman Filter(UKF)method followed by a numerical simulation experiment is performed under STK and MATLAB.Results demonstrate that the method is feasible,effective and has good convergence.Under disturbance condition,its determination accuracy in 200 m is an angle second level for the relative attitude and a millimeter level for the relative position,which meets the requirements of determining the relative state between two satellites in a shorter distance.

Published
2013

38. A Cooperative Navigation Estimation Method in Distributed Satellite System.

Author

WANG Xiao-chu, YOU Zheng, ZHAO Kai-chun, and LI Bin

Subjects
*NAVIGATION (Astronautics), *ASTRODYNAMICS, *NATURAL satellites, *ESTIMATION theory, *KALMAN filtering, *ALGORITHMS
Abstract

To solve the cooperative navigation problem for a cooperative target with distributed satellites, a cooperative navigation estimation method combined a front-end with a back-end is proposed. In the front-end, design is made by using an unscented Kalman filter modified based on the consensus algorithm. And in the back-end, design is made using a covariance intersection algorithm combined with a fast covariance intersection weighting method and an additive fusion method for non-additive parameters. Numerical simulation is done with the help of STK and MATLAB, and the validness of the proposed method is demonstrated. [ABSTRACT FROM AUTHOR]

Published
2013
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