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An improved unscented Kalman filter for satellite tracking
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Paper Abstract

In order to detect satellite under sky background, we propose an optimized satellite object detection extraction and tracking algorithm under the sky background. The proposed satellite tracking processing consists of two stages. In the first stage of object detection and extraction, the background template based on the mixture Gaussian model is used to establish background frame, and then the background is removed by inter-frame difference method to obtain the object. In the subsequent object tracking stage, this paper proposes an improved untracked Kalman filter algorithm for object tracking. Firstly, it tracks multiple suspected objects in the background, and then introduces a path coherence function to eliminate the false objects. Compared with other methods, the experimental results show that our method can better meet the real-time requirement, eliminate false objects appeared in the sequence of images more efficiently and make the tracking trajectory smoother.

Paper Details

Date Published: 12 December 2018
PDF: 9 pages
Proc. SPIE 10846, Optical Sensing and Imaging Technologies and Applications, 108460I (12 December 2018); doi: 10.1117/12.2503798
Show Author Affiliations
Zhenyu Zhu, Beijing Institute of Technology (China)
Qiong Wu, Beijing Institute of Technology (China)
Kun Gao, Beijing Institute of Technology (China)
Youwen Zhuang, Beijing Institute of Technology (China)
Jing Wang, Beijing Institute of Environmental Characteristics (China)
Guangping Wang, Beijing Institute of Environmental Characteristics (China)


Published in SPIE Proceedings Vol. 10846:
Optical Sensing and Imaging Technologies and Applications
Mircea Guina; Haimei Gong; Jin Lu; Dong Liu, Editor(s)

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