Leake Carl, Arnas David, Mortari Daniele
Aerospace Engineering, Texas A&M University, College Station, TX 77843, USA.
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Sensors (Basel). 2020 May 9;20(9):2697. doi: 10.3390/s20092697.
This study introduces a new "Non-Dimensional" star identification algorithm to reliably identify the stars observed by a wide field-of-view star tracker when the focal length and optical axis offset values are known with poor accuracy. This algorithm is particularly suited to complement nominal lost-in-space algorithms, which may identify stars incorrectly when the focal length and/or optical axis offset deviate from their nominal operational ranges. These deviations may be caused, for example, by launch vibrations or thermal variations in orbit. The algorithm performance is compared in terms of accuracy, speed, and robustness to the Pyramid algorithm. These comparisons highlight the clear advantages that a combined approach of these methodologies provides.
本研究引入了一种新的“无量纲”恒星识别算法，当焦距和光轴偏移值精度较差但已知时，该算法能够可靠地识别宽视场恒星跟踪器观测到的恒星。该算法特别适合于补充标称的空间迷失算法，当焦距和/或光轴偏移偏离其标称工作范围时，标称算法可能会错误地识别恒星。例如，这些偏差可能是由发射振动或轨道上的热变化引起的。将该算法的性能在准确性、速度和对金字塔算法的鲁棒性方面进行了比较。这些比较突出了这些方法的组合方法所具有的明显优势。
