Application of the sun line-of-sight vector in the optimal attitude estimation of deep-space probe

来源 :Journal of Harbin Institute of Technology | 被引量 : 0次 | 上传用户:sam4567
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This paper proposed an optimal algorithm using the sun line-of-sight vector to improve the probe attitude estimation accuracy in deep-space mission.Firstly,the elaborate analysis of the attitude estimation error from vector observations was done to demonstrate that the geometric relation between the reference vectors is an important factor which influences the accuracy of attitude estimation.Then,with introduction of the sun line-of-sight vector,the attitude quaternion obtained from the star-sensor was converted into a pair of mutually perpendicular reference vectors perpendicular to the sun vector.The normalized weights were calculated according to the accuracy of the sensors.Furthermore,the optimal attitude estimation in the least squares sense was achieved with the quaternion estimation method.Finally,the results of simulation demonstrated the validity of the proposed optimal algorithm based on the practical data of the Deep Impact mission. This paper proposed an optimal algorithm using the sun line-of-sight vector to improve the probe attitude estimation accuracy in deep-space mission. Firstly, the elaborate analysis of the attitude estimation error from vector observations was done to demonstrate that the geometric relation between the reference vectors is an important factor which influences the accuracy of attitude estimation. Chen, with introduction of the sun line-of-sight vector, the attitude quaternion obtained from the star-sensor was converted into a pair of parallel perpendicular reference vectors perpendicular to the sun vector.The normalized weights were calculated according to the accuracy of the sensors.Furthermore, the optimal attitude estimation in the least squares sense was achieved with the quaternion estimation method .Finally, the results of simulation demonstrated the validity of the proposed optimal algorithm based on the practical data of the Deep Impact mission.
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