Optimal attitude estimation algorithm based on mulitiple star-sensor observations
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摘要: 多数利用星敏感器加陀螺组合的姿态确定方法中,由于星敏感器精度较高,使得系统定姿的精度比较高.然而,姿态确定的算法因观测模型和误差处理不当,导致滤波器观测修正能力下降,从而不能有效地估计陀螺的漂移误差.提出了基于星敏感器观测姿态角的误差建模,研究了多星敏感器组合的最优安装构型和观测融合方法.利用加权最小二乘法对观测数据的预处理,使观测方程定常化.再利用陀螺加星敏感器组合的扩展Kalman滤波(EKF,Extended Kalman Filtering)对航天器姿态和陀螺漂移进行估计.仿真结果表明,提出的多星敏感器最优组合的滤波方法能够有效精确地估计卫星三轴姿态和陀螺漂移,且该方法计算量小,有利于卫星定姿系统的在轨自主运行.Abstract: In most of attitude determinations with methods by using the combination of star-sensors and gyros, the accuracy of attitude determination is high due to the high accuracy of star sensors. However, because of the improper processing of observation model and error, the observation correction ability of attitude filter decreases and the gyro drift error can't be estimated efficiently. Error modeling was proposed based on attitude angle observations, and the optimum installation configurations and observation syncretizing methods were investigated. By making use of the weighted least squares(WLS) preprocessing of observation data, the observation equation changed to be constant. Then, the spacecraft attitude and gyro drift were estimated by using extended Kalman filtering(EKF) with the combination of star-sensors and gyros. The simulation results show the attitude and gyro drift can be estimated accurately by using the presented filter. This method is with less the amount of calculation and of advantage to autonomous on-orbit operation of actual attitude determination system.
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Key words:
- multiple star-sensors /
- error modeling /
- optimum configurations /
- covariance matrix /
- syncretizing
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