星敏感器高动态下自主星跟踪算法

Autonomous star tracking algorithm with high dynamic spacecraft

  • 摘要: 当飞行器大角速度机动时,采用传统的星跟踪算法来提取星像坐标时,必须选取较大的扫描星图区域,从而增加了区域内包含其它星像部分像元或全部像元的可能,需要多次采用星对角距比较来选取正确的星像坐标,因此,在选取正确的星像坐标时增加了误匹配的可能。为此,文中提出一种星敏感器高动态下自主星跟踪算法,首先根据前邻时刻的瞬时姿态来预测下一时刻的输出姿态,再利用预测姿态预测当前时刻恒星在下一时刻的星像坐标,最后扫描在以预测的星像坐标为中心的星图范围内提取实际的恒星星像坐标。这样克服了采用传统星跟踪算法带来的数据更新率低、可能误匹配高甚至不能提取正确地星像坐标的缺点。最后,采用该方法进行了仿真验证以及外场观星试验。

     

    Abstract: The number of pixels scanned in star image can be large with conventional star tracking algorithm under large maneuvering of the vehicle. The feasibility of irrelevant star within threshold scan windows is increased. And the number of calculating angular separation between two stars is increased. This results in the decreasing of the update rate of star sensor. Therefore, the feasibility of error stars from star image is increased. Above all, an autonomous star tracking algorithm with high angle velocity was presented in this paper. Firstly, the next frame potential attitude was estimated according to previous attitudes. Secondly, the next frame ideal star centriodings of stars in FOV was calculated according to the potential attitude. Finally, all the real star centriodings would be obtained within the threshold scan windows of the ideal star centriodings. This algorithm can not only improve update rate of star sensor, but also avoid fault star pattern recognition. At last, the algorithm was tested by simulation and night sky experiment. The algorithm will be applied star sensor of satellite GNC.

     

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