Research on recognition and tracking technology for a fully autonomous and agile response anti LLS-target system

Keya Liu; Zijia Guo; Jingyu Liu

doi:10.1117/12.2504203

31 August 2018 Research on recognition and tracking technology for a fully autonomous and agile response anti LLS-target system

Keya Liu, Zijia Guo, Jingyu Liu

Author Affiliations +

Proceedings Volume 10835, Global Intelligence Industry Conference (GIIC 2018); 1083511 (2018) https://doi.org/10.1117/12.2504203
Event: Global Intelligent Industry Conference 2018, 2018, Beijing, China

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.

Citation Download Citation

Keya Liu, Zijia Guo, and Jingyu Liu "Research on recognition and tracking technology for a fully autonomous and agile response anti LLS-target system", Proc. SPIE 10835, Global Intelligence Industry Conference (GIIC 2018), 1083511 (31 August 2018); https://doi.org/10.1117/12.2504203

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