基于VMD的广义二次互相关时延估计方法  

Time Delay Estimation Method of Generalized Second Cross Correlation Based on VMD

作　　者：李宏[1] 田雷 路敬祎[2,3] 刘庆强[1] LI Hong;TIAN Lei;LU Jingyi;LIU Qingqiang(School of Electrical Engineering and Information,Northeast Petroleum University,Daqing 163318,China;Artificial Intelligence Energy Research Institute,Northeast Petroleum University,Daqing 163318,China;Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control,Northeast Petroleum University,Daqing 163318,China)

机构地区：[1]东北石油大学电气信息工程学院,黑龙江大庆163318 [2]东北石油大学人工智能能源研究院,黑龙江大庆163318 [3]东北石油大学黑龙江省网络化重点实验室,黑龙江大庆163318

出　　处：《吉林大学学报（信息科学版）》2021年第3期260-266,共7页Journal of Jilin University（Information Science Edition）

基　　金：国家重大科技专项基金资助项目(2017ZX05019-005);黑龙江省自然科学基金资助项目(LH2019F004)。

摘　　要：针对广义互相关(GCC:Generalized Cross-Correlation)时延估计方法在低信噪比的情况下会产生较大误差的问题,提出一种基于变分模态分解(VMD:Variational Mode Decomposition)结合广义二次互相关(GSCC:Generalized Second Cross-Correlation)进行时延估计的方法。该方法首先对两路信号分别进行变分模态分解,分离有效模态和噪声模态,使用豪斯多夫距离(HD:Hausdorff Distance)优选模态并重构信号,然后运用广义二次互相关对处理后的信号进行时延估计。理论分析和仿真实验结果表明,与广义二次互相关方法、小波去噪结合广义二次互相关(WT-GSCC:Wavelet-GSCC)方法比较,该方法能有效提升估计精度,具有良好的抗噪性能。Aiming at the problem that the GCC( Generalized Cross-Correlation) time delay estimation method will produce large errors under the condition of low signal-to-noise ratio,a method of time delay estimation based on VMD( Variational Mode Decomposition) combined with GSCC( Generalized Second Cross-Correlation) is proposed. This method first performs variational modal decomposition of the two signals separately,separates the effective mode and the noise mode,uses the HD( Hausdorff Distance) to optimize the mode and reconstructs the signal. Then uses the generalized second cross-correlation to analyze the processed signal and perform delay estimation. Theoretical analysis and simulation experiment results show that compared with the generalized second cross-correlation method, wavelet denoising combined with the generalized second cross-correlation( WT-GSCC: Wavelet-GSCC) method,this method can effectively improve the estimation accuracy and has good anti-noise performance.

关 键 词：变分模态分解 广义二次互相关 豪斯多夫距离 时延估计 

分 类 号：TN911.72[电子电信—通信与信息系统]