基于VMD的激光雷达回波信号去噪方法研究

为滤除激光雷达回波信号中的噪声,提高其信噪比,本文提出了一种基于变分模态分解(VMD)的回波信号去噪方法。该方法利用去趋势波动分析对信号进行变分模态分解,通过巴氏距离区分相关模态和非相关模态,采用移动平均法提取非相关模态中的有用信号,并将其与相关模态进行重构实现噪声的有效去除。实验结果表明,经该方法处理后的回波信号输出信噪比提高到了22.58 dB,均方根误差减小为0.78×10-11。该方法能有效滤除激光雷达回波信号中的噪声,保证信号的完整性,与小波变换、经验模态分解直接阈值、变分模态分解局部重构等方法相比,具有明显优势。

De-noising method research for lidar echo signal based on variational mode decomposition

To filter the noise in the lidar echo signal and improve its signal-to-noise ratio,a de-noising method of echo signal based on variational mode decomposition (VMD) is proposed.This method uses detrended fluctuation analysis to decompose the signal through VMD,and the relevant and irrelevant modes are distinguished by Bhattacharyya distance.Then,the moving average is used to extract useful signals from the irrelevant modes,and the effective removal of the noise is realized by reconstructing it with the relevant modes.The experimental results show that the output signal-to-noise ratio is increased to 22.58 dB,and the root mean square error is reduced to 0.78×10-11 by this method,which could effectively filter the noise of lidar echo signal and guarantee the integrity of the signal.Compared with wavelet transform,empirical mode decomposition with direct thresholding and variational mode decomposition partial reconstruction,this method has obvious advantages.