针对多旋翼无人机目标的识别问题，提出一种基于伽柏（Gabor）变换的瞬时频率估计与快速傅里叶变换（FFT）相结合的微多普勒特征提取算法。首先建立多旋翼无人机旋翼回波模型，并通过仿真分析叶片数目、旋翼转速和初始相位等参数对微多普勒特征的影响，利用Gabor变换得到时频特征。在此基础上通过瞬时频率极大值法提取微多普勒频率，并对瞬时频率采用FFT提取旋翼数和转动频率，从而获得叶片长度估计值。实测数据验证了该算法较为准确地提取无人机的微多普勒参数。
In order to solve the problem of multi-rotor UAV target recognition, a micro-Doppler feature extraction algorithm based on Gabor transform is proposed by combining the instantaneous frequency estimation and fast Fourier transform(FFT). Firstly, the echo model of multi-rotor UAV is established, and the analysis of the influences of number of blades, rotor speed, and initial phase on the micro-Doppler characteristics is made by simulation. Then, Gabor transform is adopted to obtain time-frequency feature. Based on this, micro-Doppler frequency is extracted by the instantaneous frequency maximum value method, and the FFT of instantaneous frequency is used to extract rotor number and rotational frequency. With the above information, the length of the blade is calculated. Finally, the measured data for "Phantom 3S" show that the proposed algorithm extracts the micro-Doppler parameters accurately, indicating the effectiveness of the algorithm.
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