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Proceedings Paper

Interference and deception detection technology of satellite navigation based on deep learning
Author(s): Weiyi Chen; Pingke Deng; Yi Qu; Xiaoguang Zhang; Yaping Li
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Paper Abstract

Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

Paper Details

Date Published: 24 October 2017
PDF: 9 pages
Proc. SPIE 10463, AOPC 2017: Space Optics and Earth Imaging and Space Navigation, 1046302 (24 October 2017); doi: 10.1117/12.2283006
Show Author Affiliations
Weiyi Chen, Academy of Opto-Electronics (China)
Univ. of Chinese Academy of Sciences (China)
Pingke Deng, Academy of Opto-Electronics (China)
Univ. of Chinese Academy of Sciences (China)
Yi Qu, Academy of Opto-Electronics (China)
Xiaoguang Zhang, Academy of Opto-Electronics (China)
Yaping Li, Academy of Opto-Electronics (China)


Published in SPIE Proceedings Vol. 10463:
AOPC 2017: Space Optics and Earth Imaging and Space Navigation
Carl Nardell; Suijian Xue; Huaidong Yang, Editor(s)

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