【摘要】 针对激光雷达回波信号较弱易于被各种噪声污染的特点,本文提出利用经验模态来模态分解(EMD)这一非线性、非平稳信号处理方法,对Mie散射激光雷达信号进行多尺度分解。该方法是利用信号内部时间尺度的变化做能量与频率的解析,采用这种方法能够将噪声污染的激光雷达信号分解成若干个线性、稳态的本征函数(IMF),通过对本征函数的重构,去除包含高频噪声的IMFs,从而达到去噪目的。实验结果表明,这种方法的去噪能力强,并且具有自适应的特点,从而说明了这种方法在信号去噪中的优势。更多还原

【Abstract】 In view of lidar return signal easily polluted by various noises, a new method of Empirical Mode Decomposition (EMD) that can analyze the nonlinear and non-stationary signal is introduced to decompose lidar signal. The method based on signal intrinsic time scales is used to extract the energy and frequency of signal. With the method, the Mie lidar signal polluted by noises is decomposed into a number of Intrinsic Mode Function (IMF). In the reconstruction course of IMFs, the IMFs including high-frequency noise are excluded to reduce the noise. The experiment results demonstrate that the method has powerful and adaptive de-noising ability. To denoise Mie lidar signal by using the method has been attempted. It is believed that the method can provide a new effective way of noise reduction for weak lidar signal.更多还原