Detection and recognition of UA targets with multiple sensors

被引:0
|
作者
Chen, W.S. [1 ]
Chen, X.L. [2 ]
Liu, J. [3 ]
Wang, Q.B. [1 ]
Lu, X.F. [1 ]
Huang, Y.F. [1 ]
机构
[1] China Academy of Civil Aviation Science and Technology, Beijing,100028, China
[2] Naval Aviation University, Yantai,264001, China
[3] Beihang University, Beijing,100191, China
来源
Aeronautical Journal | 2023年 / 127卷 / 1308期
关键词
Aircraft detection - Contrastive Learning - Deep learning - Information fusion - Radar target recognition - Sensor data fusion - Unmanned aerial vehicles (UAV);
D O I
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中图分类号
学科分类号
摘要
Modern low-altitude unmanned aircraft (UA) detection and surveillance systems mostly adopt the multi-sensor fusion technology scheme of radar, visible light, infrared, acoustic and radio detection. Firstly, this paper summarises the latest research progress of UA and bird target detection and recognition technology based on radar, and provides an effective way of detection and recognition from the aspects of echo modeling and micro motion characteristic cognition, manoeuver feature enhancement and extraction, motion trajectory difference, deep learning intelligent classification, etc. Furthermore, this paper also analyses the target feature extraction and recognition algorithms represented by deep learning for other kinds of sensor data. Finally, after a comparison of the detection ability of various detection technologies, a technical scheme for low-altitude UA surveillance system based on four types of sensors is proposed, with a detailed description of its main performance indicators. © The Author(s), 2022. Published by Cambridge University Press on behalf of Royal Aeronautical Society.
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页码:167 / 192
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