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Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm 被引量:1
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作者 Peerapong Torteeka Peng-Qi Gao +5 位作者 Ming Shen Xiao-Zhang Guo Da-Tao Yang Huan-Huan Yu Wei-Ping Zhou You Zhao 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2017年第2期51-62,共12页
Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static b... Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia- Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle- filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking. 展开更多
关键词 astrometry -- space debris -- atmospheric effects -- image processing
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