在振动目标的激光微多普勒信号分析中,基于联合时频谱的分析方法为目标的检测、分类和识别提供有用信息,得到广泛运用。对于一般非线性和非平稳信号,传统的时频分析方法能有效地提取信号特征,但在强背景噪声和弱调制信道条件下,具有很大局限性。引入希尔伯特-黄变换(HHT)作为一种新的微多普勒信号分析方法,分析在强背景噪声和弱调制等信道下,HHT在微多普勒信号中的特征提取。通过Matlab软件仿真,与平滑伪Wigner-Ville分布(SPWVD)比较,证明了HHT在微多普勒信号分析和特征提取中的有效性。 In the micro-Doppler laser signal analysis of vibration targets, the method based on joint time-frequency spectrum provides useful information for the detection, classification and identification of targets and is widely used. For general nonlinear and non-stationary signals, the traditional time-frequency analysis method can effectively extract signal features, but it has great limitations under strong background noise and weak modulation channel conditions. The Hilbert-Huang Transform (HHT) is introduced as a new micro-Doppler signal analysis method to analyze the feature extraction of HHT in micro-Doppler signals under strong background noise and weak modulation. By comparing with the smoothed pseudo-Wigner-Ville distribution (SPWVD) by Matlab software simulation, the validity of HHT in micro-Doppler signal analysis and feature extraction is proved.