Method of space object detection by wide field of view telescope based on its following error

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.