基于变分模态分解和奇异谱分析的GPR信号去噪  

Noise Reduction Method of GPR Signal Based on VMD-SSA

作　　者：戴前伟[1,2] 丁浩 张华[1,2] 张豪 Dai Qianwei;Ding Hao;Zhang Hua;Zhang Hao(School of Geosciences and Info-Physics,Central South University,Changsha410083,China;Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring,Ministry of Education,Changsha410083,China)

机构地区：[1]中南大学地球科学与信息物理学院,长沙410083 [2]有色金属成矿预测与地质环境监测教育部重点实验室,长沙410083

出　　处：《吉林大学学报（地球科学版）》2022年第3期701-712,共12页Journal of Jilin University：Earth Science Edition

基　　金：国家自然科学基金项目(41874148);国家重点研发计划项目(2018YFC0603903)。

摘　　要：受设备及环境等因素的主要影响,采集的探地雷达(GPR)信号中存在不同程度的噪声干扰.传统变分模态分解(VMD)通过搜寻变分模型最优解分离出不同中心频率的分量实现噪声压制,但最优模态数的选择具有一定主观性,致使重构数据存在不同程度的信号振荡.为优化模态数的选择,并改善信号振荡问题,本文提出基于自适应VMD和奇异谱分析(SSA)的GPR信号去噪方法.首先,引入能量损失比,实施最优模态数的自适应选择,并利用皮尔逊相关系数法提取有效信号;其次,针对变分模态分解后的中低频振荡现象,引入SSA进行二次滤波,进一步提高信噪比.合成Ricker子波实验、合成雷达剖面模拟实验和实测资料验证了变分模态分解奇异谱分析(VMD SSA)方法的有效性.合成Ricker子波实验中,与集成经验模态分解(EEMD)和传统VMD方法相比,经VMD SSA方法处理后的信噪比最大提升13.5878dB;合成雷达剖面模拟实验中,基于VMD SSA方法处理后剖面的信噪比较EEMD和传统VMD方法分别提高3.7659dB和2.6557dB;实测资料处理中也较好地压制了背景噪声及随机噪声,使异常体的信号特征更加突出.Due to the influence of equipment and environmental factors,the signals collected by ground-penetrating radar(GPR)are vulnerable to varying degrees of noise interference.Traditional variational mode decomposition(VMD)suppresses noise by searching for the optimal solution of variational modes to separate the components with different center frequencies.However,the selection of optimal mode number is challenging and subjective,resulting in the reconstructed signals being affected by different degrees of oscillation.To solve these problems,we proposed a combined denoising method based on the adaptive VMD and singular spectrum analysis(SSA).Firstly,the energy loss ratio is defined to facilitate the adaptive selection of the optimal mode number,and the Pearson correlation coefficient method is employed to extract the valid signal.Secondly,to solve the problem of the low-frequency oscillation phenomenon in VMD,SSA is further used to perform secondary filtering to improve the signal-to-noise ratio(R_(SN)).The effectiveness of the proposed method is verified by the synthetic wavelet experiment,numerical simulation experiment,and field experiment.In the synthetic wavelet experiment,the SNR of VMD-SSA processing is improved maximum by 13.5878 dB over the ensemble empirical mode decomposition(EEMD)and the traditional VMD methods;in the numerical simulation experiment,the SNR of the processed B-scan using the VMD-SSA method is improved by 3.7659 dB and 2.6557 dB respectively compared with the EEMD and traditional VMD methods;in addition,the background noise and the random noise are also properly suppressed in the field data processing.The proposed method not only solves the oscillation problem but also highlights the features of the abnormal signals more effectively.

关 键 词：探地雷达(GPR) 变分模态分解(VMD) 能量损失比 奇异谱分析(SSA) 信号去噪 

分 类 号：P631[天文地球—地质矿产勘探]