Research on radar target track recognition based on convolutional neural network

Fan Yuqi; Wen Pengfei; Xu Xiong; Guo Dan; Liu Yulan

doi:10.11884/HPLPB201931.180388

Volume 31 Issue 9

Sep. 2019

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Article Navigation > High Power Laser and Particle Beams > 2019 > 31(9): 093203

Fan Yuqi, Wen Pengfei, Xu Xiong, et al. Research on radar target track recognition based on convolutional neural network[J]. High Power Laser and Particle Beams, 2019, 31: 093203. doi: 10.11884/HPLPB201931.180388

Citation:

Fan Yuqi, Wen Pengfei, Xu Xiong, et al. Research on radar target track recognition based on convolutional neural network[J]. High Power Laser and Particle Beams, 2019, 31: 093203. doi: 10.11884/HPLPB201931.180388

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Research on radar target track recognition based on convolutional neural network

doi: 10.11884/HPLPB201931.180388

Fan Yuqi^{1, 3
,},
Wen Pengfei^{1, 2},
Xu Xiong²,
Guo Dan¹,
Liu Yulan¹

1.
School of Computer and Information, Hefei University of Technology, Hefei 230009, China
2.
State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang 471003, China
3.
Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei 230009, China

Received Date: 2018-12-31
Rev Recd Date: 2019-06-27
Publish Date: 2019-09-15

Abstract

Abstract

A large number of various radar signals in modern warfare make the electromagnetic environment more and more complex. It is urgent to quickly and accurately obtain the category information of the target track from a large number of radar data, and provide accurate and effective information for the battlefield command. The traditional radar-based target recognition method based on human experience or cognition is unable to effectively cope with the ever-changing battlefield and massive data. Based on the characteristics of actual radar data, this paper proposes a logarithmic preprocessing method and constructs a deep learning model based on convolutional neural network. The deep learning model realizes the recognition and detection of the target track in radar confrontation. The built model is tested based on the radar target track data generated by the simulation. Experiments show that the model can effectively detect and identify the target track.
- radar confrontation,
- electronic warfare,
- target detection,
- logarithmic preprocessing,
- convolutional neural network

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References(10)

References

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