Fixed-Wing UAV Detection Based on Simulated Data Transfer Learning

Authors

Yu Fu, 1.Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin 300384, China;2.School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;Follow
Yao Zhang, 1.Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin 300384, China;2.School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;Follow
Meng Zhao, 1.Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin 300384, China;2.School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;
Mianzhao Wang, 1.Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin 300384, China;2.School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;
Jiangpeng Zheng, 1.Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin 300384, China;2.School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;
Chen Jia, 1.Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin 300384, China;2.School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;
Shengyong Chen, 1.Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin 300384, China;2.School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China;

Abstract

Abstract: Data play an important role in visual inspection tasks, but it is difficult to obtain a sufficient amount of real fixed-wing UAV data. Therefore, a data set containing a large number of simulated fixed-wing UAV data and a small number of real fixed-wing UAV data is constructed, and the real fixed-wing UAV data are detected by training simulated fixed-wing UAV data based on the idea of weight transfer. On this basis, a two-stage learning strategy is proposed to further reduce the missed detection rate of UAVs by using multi-scale feature fusion.The simulation results show that simulated data can be used to detect real fixed-wing UAVs, which has potential application prospects in future target detection research.

Recommended Citation

Fu, Yu; Zhang, Yao; Zhao, Meng; Wang, Mianzhao; Zheng, Jiangpeng; Jia, Chen; and Chen, Shengyong (2023) "Fixed-Wing UAV Detection Based on Simulated Data Transfer Learning," Journal of System Simulation: Vol. 35: Iss. 5, Article 9.
DOI: 10.16182/j.issn1004731x.joss.22-0024
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss5/9

First Page

998

Revised Date

2022-02-22

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.22-0024

Last Page

1007

CLC

TP391.9

Recommended Citation

Yu Fu, Yao Zhang, Meng Zhao, Mianzhao Wang, Jiangpeng Zheng, Chen Jia, Shengyong Chen. Fixed-Wing UAV Detection Based on Simulated Data Transfer Learning[J]. Journal of System Simulation, 2023, 35(5): 998-1007.

Corresponding Author

Yao Zhang,zytju221@tju.edu.cn

DOI

10.16182/j.issn1004731x.joss.22-0024