Robustness Study of Non-Dimensional Star Pattern Recognition for a Typical Star Tracker

Non-Dimensional star pattern recognition uses planar angles as its recognition feature. This feature is independent of image focal length and optical axis offset. However, this independency doesn’t mean that the algorithm conserves its robustness in presence of any type of errors. These errors arise from poor hardware calibration and software inaccuracy that causes the angles to differ from their true amounts stored in the database. In order to evaluate the effect of angle differences on algorithm performance, overall disposition of bright point centers is modeled. The monte-carlo simulation method is then used to evaluate the algorithm’s performance for different amounts of error. Results demonstrate that ۰.۱ pixel size error is admissible in conserve the trade-off between desired update frequency, hardware accuracy and algorithm’s robustness.對於典型的星盈無量綱星模式識別魯棒性研究摘要無量綱星圖識別使用平面的角度作為其識別功能。此功能是獨立的圖像焦距和光軸偏移。然而，這種獨立性並不意味著該算法節省其魯棒性的任何類型的錯誤的存在。從差硬件校準和軟件不精確導致該角度從存儲在數據庫中的真實量不同出現這些錯誤。為了評估對算法性能的角度差異的影響，亮點中心的整體配置為藍本。然後蒙特卡羅仿真方法用於評估算法對不同量的誤差的性能。結果表明，۰.۱像素尺寸誤差在養護所需的更新頻率，硬件精度和算法的魯棒性之間的權衡受理。

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K.N.Tossi university of technology , en