摘要
为了进一步提高探地雷达(ground penetrating radar,GPR)数据的信噪比,压制由随机扰动引起的随机绕射能量,将二维变分模态分解(two-dimensional variational mode decomposition,2D-VMD)引入二维GPR数据的噪声压制处理中。首先,对GPR数据进行2D-VMD处理,并分析各阶本征模态函数(intrinsic mode function,IMF)分量及其对应的频率-波数域谱来确定雷达剖面中的各回波类型。然后,计算IMF分量与原始数据的互相关系数来确定信号模态和噪声模态,并对信号模态进行重构得到降噪后的数据。理论数据和实测数据测试表明,相比于传统的1D-VMD法,2D-VMD滤波后的含噪正演记录峰值信噪比由6.44 dB增加到7.72 dB;经2D-VMD降噪处理后的雷达剖面在保留有效信号的基础上,可以有效压制随机扰动带来的噪声,并且得到的雷达剖面同相轴连续性更好。
In order to improve the signal-to-noise ratio(SNR)of ground penetrating radar(GPR)data and reduce the random diffraction energy caused by random perturbation,two-dimensional variational mode decomposition(2D-VMD)is introduced into the noise reduction processing of 2D GPR data.First,the GPR data is processed by 2D-VMD,and the intrinsic mode function(IMF)components and their corresponding frequency and wave number spectra are analyzed to determine the type of each echo showed in the radar profile.Then,the cross-correlation coefficients between the IMF components and the original data are calculated to determine the signal mode and noise mode,and the signal mode is reconstructed to obtain data after noise reduction.Synthetic and practical data tests demonstrate that compared with the traditional 1D-VMD method,the peak SNR of the forward recording with noise after 2D-VMD filtering increases from 6.44 dB to 7.72 dB.The newly developed method can get significantly improvement on the SNR of GPR data,and obtain radar profiles with better event continuity.
作者
刘财
商耀达
鹿琪
徐杨杨
Liu Cai;Shang Yaoda;Lu Qi;Xu Yangyang(College of GeoExploration Science and Technology,Jilin University,Changchun 130026,China;Key Laboratory of Applied Geophysics,Ministry of Natural Resources,Changchun 130026,China;National Engineering Research Center of Offshore Oil and Gas Exploration,Changchun 130026,China)
出处
《吉林大学学报（地球科学版）》
CAS
CSCD
北大核心
2024年第3期1042-1053,共12页
Journal of Jilin University：Earth Science Edition
基金
国家自然科学基金项目(41874125)
吉林省科技发展计划项目(20200201045JC)。
关键词
探地雷达
二维变分模态分解
频率-波数谱
互相关系数
去噪
ground penetrating radar(GPR)
two-dimensional variational modal decomposition(2D-VMD)
frequency and wave number spectrum
cross-correlation coefficient
noise reduction
