Ye Tao, Zhou Fuqiang
Appl Opt. 2015 Apr 10;54(11):3455-69. doi: 10.1364/AO.54.003455.
When imaged by detectors, space targets (including satellites and debris) and background stars have similar point-spread functions, and both objects appear to change as detectors track targets. Therefore, traditional tracking methods cannot separate targets from stars and cannot directly recognize targets in 2D images. Consequently, we propose an autonomous space target recognition and tracking approach using a star sensor technique and a Kalman filter (KF). A two-step method for subpixel-scale detection of star objects (including stars and targets) is developed, and the combination of the star sensor technique and a KF is used to track targets. The experimental results show that the proposed method is adequate for autonomously recognizing and tracking space targets.
当通过探测器成像时，空间目标（包括卫星和碎片）与背景恒星具有相似的点扩散函数，并且随着探测器跟踪目标，这两种物体看起来都会发生变化。因此，传统的跟踪方法无法将目标与恒星分离，也无法直接在二维图像中识别目标。为此，我们提出了一种利用星敏感器技术和卡尔曼滤波器（KF）的自主空间目标识别与跟踪方法。开发了一种用于亚像素尺度检测星状物体（包括恒星和目标）的两步法，并利用星敏感器技术和卡尔曼滤波器的组合来跟踪目标。实验结果表明，该方法足以自主识别和跟踪空间目标。
