特征提取
时频分析
霍夫变换
特征(语言学)
多普勒效应
雷达
转子(电动)
声学
多普勒雷达
刀(考古)
人工智能
雷达截面
直升机旋翼
计算机科学
信号(编程语言)
工程类
模式识别(心理学)
物理
航空航天工程
语言学
结构工程
程序设计语言
哲学
天文
图像(数学)
机械工程
作者
Xiaoli Fang,Guoqing Xiao
出处
期刊:IEEE Sensors Journal
[Institute of Electrical and Electronics Engineers]
日期:2021-02-01
卷期号:21 (3): 3592-3601
被引量:8
标识
DOI:10.1109/jsen.2020.3027373
摘要
In this article, the micro-Doppler feature analysis and extraction of small unmanned rotorcraft (SUR) is considered. To be specific, the radar returns from the rotor blades are first modeled as sinusoidal frequency-modulated (SFM) signals. Then, the Gabor transform is utilized to obtain the time-frequency distribution (TFD). In order to solve the problem of limited TF analysis resolutions, high carrier frequency of radar is employed for the sake of separating different sinusoidal curves from TFD. After that, the Hough-Radon transform (HRT) is introduced to detect the sinusoidal curves from the TFD. Finally, based on the relationship between the SFM signal and the rotating blade, the micro-Doppler parameters which can reflect the threat level of the SUR to a large extend are estimated. Compared with other existing methods, the proposed method presents the relationships between the carrier frequency and the rotating blade parameters and it can be employed to extract the micro-Doppler feature of SUR with multiple rotor hubs. Simulation results demonstrate the effectiveness of the proposed micro-Doppler feature extraction method.
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