由于星敏感器仅仅工作在全天球的识别模式下远不能满足当前飞行器任务的需要,提出了当星敏感器有足够的先验信息情况下,可在星跟踪模式或者预测星像模式下工作,来提高星敏感器的数据更新率,降低由全天球识别带来误匹配的可能性.本文提出了一种新的星跟踪算法来克服飞行器在大角速度飞行情况下传统星跟踪算法处理时间过长等不足;为了消除由于系统噪声带来的误差,还提出了星图滤波和星像滤波的方法.实验结果表明,当飞行器在2.25°/s的角速度下飞行时,星敏感器能在10 pixel×10 pixel的范围内从星图中正确提取星像,星图经去噪后,星敏感器输出精度提高了近5″,从而使星敏器可在飞行器高动态飞行情况下实现高精度、高更新率的姿态输出.文中描述的所有方法已在2007年和2008年进行了地面观星测试,并于2009年即将应用于某些卫星的姿控系统中.%Star sensors may work in star tracking cases and predictive centroiding algorithm cases when it has sufficient attitude knowledge, which not only can increase the update rates of star sensors, but also can improve recognition performance. A novel star tracking algorithm for a star sensor with a large angle manoeuver is presented to avoid disadvantages of classic star tracking algorithms. In order to decrease noise errors of the star sensor, the filtering algorithms for star images and star locations are presented. The experimental results show that the star locations are obtained in the threshold scan window 10 pixel×10 pixel in the star image and the attitude accuracy of the star sensor is improved by 5″ in the star image filtered by C-L wavelet, when the spacecrafts are rolled with a angle velocity of 2.25°/s. These algorithms are tested at night sky experiments in 2007 and in 2008 and will be used in the attitude control system of a satellite in 2009.
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