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Research on recognition and tracking technology for a fully autonomous and agile response anti LLS-target system
Author(s): Keya Liu; Zijia Guo; Jingyu Liu
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Paper Abstract

Counteracting LSS-Target (the Low altitude, Slow speed Small Target) has become a hot topic in security field in recent years. However, some technical means are not fully mature. A kind of fully autonomous and agile response anti-LSS-Target system has been proposed. Through one approach based on deep learning, a convolution neural network (CNN) is constructed and trained to realize the effective recognition of UAV. The tracking model of UAV is built based on discrete Kalman filter algorithm to achieve long-term tracking in the field of view. The test results show that after identifying the target UAV automatically, the system locks the target and tracks it steadily.

Paper Details

Date Published: 31 August 2018
PDF: 7 pages
Proc. SPIE 10835, Global Intelligence Industry Conference (GIIC 2018), 1083511 (31 August 2018); doi: 10.1117/12.2504203
Show Author Affiliations
Keya Liu, Beijing Institute of Control and Electronics Technology (China)
Zijia Guo, Beijing Institute of Control and Electronics Technology (China)
Jingyu Liu, Beijing Institute of Control and Electronics Technology (China)


Published in SPIE Proceedings Vol. 10835:
Global Intelligence Industry Conference (GIIC 2018)
Yueguang Lv, Editor(s)

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