Abstract
AbstractIn the past few years, the increasing amount of space debris has triggered the demand for distributed surveillance systems. Long exposure time can effectively improve the target detection capability of the wide-area surveillance system. Problems that also cause difficulties in space-target detection include large amounts of data, countless star points, and discontinuous or nonlinear targets. In response to these problems, this paper proposes a high-precision space-target detection and tracking pipeline that aims to automatically detect debris data in space. First, a guided filter is used to effectively remove the stars and noise, then Hough transform is used to detect space debris, and finally Kalman filter is applied to track the space debris target. All experimental images are from Jilin Observatory, and the telescope is in star-tracking mode. Our method is practical and effective. The results show that the proposed automatic extraction channel of space debris can accurately detect and track space targets in a complex background.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Space and Planetary Science,Physics and Astronomy (miscellaneous),Agricultural and Biological Sciences (miscellaneous),Biochemistry, Genetics and Molecular Biology (miscellaneous),Materials Science (miscellaneous),Medicine (miscellaneous)
Cited by
5 articles.
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