Yang Wenbo, Zhao Yan, Liu Ming, Liu Delong
Opt Express. 2021 Oct 25;29(22):35348-35365. doi: 10.1364/OE.440842.
Space objects and stars appear similar in images acquired by the wide field of view (FOV) survey telescope. This work investigates a unique property of the telescope observing a space object in satellite tracking mode, namely that the azimuth and altitude angles of the object and those of the optical axis of the telescope vary, in theory, in the same way. Based on this property we derive that the movement distance of the object between the two adjacent frames is minimal compared to the distance of the star. With this conclusion, it is possible to detect the object from a large number of background stars. To improve the robustness of the detection, the set of candidate objects is created. Finally, a clustering algorithm is employed to successfully extract the motion trajectory of the object. Unlike traditional detection methods or techniques based on image processing and analysis, our proposed detection is closely related to the parameters of the trajectory-following performance, which provides a more reliable basis for improving the detection rate. The feasibility and accuracy of the algorithm was verified by the 1.2-meter wide FOV survey telescope at the Jilin base of the Changchun observatory, with a detection rate of over 98%. The test results indicate that the method can satisfy the demand for detecting the object in an open-loop tracking. If the detection method is implemented in hardware, it can detect the object in a closed-loop tracking. As a result, it will have a wider scope for applications.
在宽视场（FOV）巡天望远镜获取的图像中，空间物体和恒星看起来很相似。这项工作研究了该望远镜在卫星跟踪模式下观测空间物体的一个独特特性，即物体的方位角和高度角与望远镜光轴的方位角和高度角在理论上以相同方式变化。基于这一特性，我们得出物体在相邻两帧之间的移动距离与恒星的距离相比是最小的。基于这一结论，就有可能从大量背景恒星中检测出该物体。为了提高检测的稳健性，创建了候选物体集。最后，采用聚类算法成功提取了物体的运动轨迹。与基于图像处理和分析的传统检测方法或技术不同，我们提出的检测方法与轨迹跟踪性能参数密切相关，这为提高检测率提供了更可靠的依据。该算法的可行性和准确性在长春天文台吉林基地的1.2米宽视场巡天望远镜上得到了验证，检测率超过98%。测试结果表明，该方法能够满足开环跟踪中检测物体的需求。如果将该检测方法在硬件中实现，它可以在闭环跟踪中检测物体。因此，它将有更广泛的应用范围。
