深空巡航CubeSat自主轨道确定
Autonomous Orbit Determination for a CubeSat Cruising in Deep Space
摘要：
立方体卫星已成为深空探索的一个有意义的选择，但必须提高其自主性，以最大限度地提高科学回报，同时限制操作的复杂性。我们在这里提出了一个解决方案的自主轨道确定的背景下，立方体卫星巡航在深空。研究案例是从地球到火星的旅程。被认为是在立方体卫星标准的光学传感器。增加了图像处理，以0.2角秒的精度提取遥远天体的方向：它包括一个多交叉相关（MCC）算法，该算法在图像背景中使用明亮的恒星。然后，建立一个无迹卡尔曼滤波器（UKF），从天体的连续方向进行异步三角测量。UKF在不可能进行线性近似的情况下满足预期性能。在地球-火星巡航的中间，轨道重建达到30公里的3-sigma精度。此外，使用典型的CubeSat硬件，滤波器的CPU成本估计为每次迭代不到1秒。它准备进一步改进与数据融合，更快的收敛和姿态控制的节省有关的新的可观测量。
英文摘要：
CubeSats have become a meaningful option for deep-space exploration, but their autonomy must be increased to maximize the science return while limiting the complexity in operations. We present here a solution for an autonomous orbit determination in the context of a CubeSat cruising in deep space. The study case is a journey from Earth to Mars. An optical sensor at CubeSat standard is considered. The image processing is added to extract the direction of distant celestial bodies with 0.2 arcsec accuracy: it consists of a Multiple Cross-Correlation (MCC) algorithm that uses bright stars in the background of the images. Then, an Unscented Kalman Filter (UKF) is built to perform an asynchronous triangulation from the successive directions of the celestial bodies. The UKF meets the expected performance in contexts where linear approximations are not possible. The orbit reconstruction reaches a 3-sigma accuracy of 30 km in the middle of the Earth-Mars cruise. Additionally, the CPU cost of the filter is assessed at less than 1 second per iteration with a typical CubeSat hardware. It is ready for further improvements in terms of new observables associated with data fusion, quicker convergence and attitude control savings.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
