Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar
Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar
复制标题
多旋翼无人机微多普勒仿真结合真实电机速度并通过 L 波段凝视雷达进行验证
DOI：
10.1109/radarconf2248738.2022.9764352
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Cameron Bennett
中科院分区：
文献类型：
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作者：
D. White;M. Jahangir;M. Antoniou;Chris Baker;J. Thiyagalingam;S. Harman;Cameron Bennett
本文推导了多旋翼无人机时间序列雷达回波的三个简单模型，并将真实的无人机电机速度记录填充到方程参数中，生成了一个合成谱图，该谱图准确捕获了螺旋桨叶片快速旋转引起的特征多普勒边带。在模型的振幅调制缺陷被识别和现象学处理。合成的无人机数据被注入到真实的雷达背景中，使用l波段凝视雷达直接比较旋翼无人机的合成和真实频谱图。
In this paper, three simple models of a multi-rotor drone's timeseries radar returns were derived, and by populating the equation parameters with genuine drone motor speed recordings, a synthetic spectrogram was generated that accurately captures the characteristic uDoppler sidebands caused by the rapidly rotating propeller blades. Deficiencies in the model's amplitude modulation were identified and phenomenologically treated. The synthetic drone data was injected into a real radar background enabling a direct comparison of synthetic and real spectrograms of rotary-wing drones with an L-band staring radar.
DOI：
10.1109/radar42522.2020.9114745
发表时间：
2020-04
期刊：
2020 IEEE International Radar Conference (RADAR)
影响因子：
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作者：
H. Dale;C. Baker;M. Antoniou;M. Jahangir
通讯作者：
H. Dale;C. Baker;M. Antoniou;M. Jahangir
无人机低信噪比雷达分类的卷积神经网络比较
DOI：
10.1109/radarconf2147009.2021.9455181
发表时间：
2021
期刊：
--
影响因子：
--
作者：
Dale H
通讯作者：
Dale H