传声器阵列特征值滤波去噪方法

作为二阶统计量的互谱矩阵(CSM)是声学成像算法的核心输入量。为增强传声器阵列的去噪表现,研究了互谱矩阵特征值滤波的机理,并提出了两种新型的特征值滤波方法的设计准则:(1)声源互谱矩阵的Stein无偏风险估计(SURE收缩),即基于SURE准则的特征值软阈值收缩;(2)进一步提高声源互谱矩阵EYM (Eckart-Young-Mirsky)估计误差的最优收缩(Opt-Shrinkage)方法,即对声源特征值所含有的噪声进一步去除。然后,在3000个快照数,0 dB信噪比(SNR),100个传声器的环境下进行仿真。通过仿真,与经典的MUSIC方法比较原声源信号与去噪后信号的互谱矩阵对角线误差,其中MUSIC方法的互谱矩阵对角线误差为74.15%,SURE收缩为41.97%,最优收缩为20.62%。并通过改变快照数、声源数与SNR,对比了不同特征值滤波去噪方法的效果。从仿真结果上看,在少声源(少于40个)工况下SURE收缩方法的去噪效果优于MUSIC方法与最优收缩方法;在声源数超过42个后,最优收缩方法取得更显著的效果。最后,在3个声源、60个传声器数、-5 dB信噪比的声源定位实验中,SURE收缩与最优收缩均获得了相比MUSIC方法更好的去噪效果。研究表明在现有传声器阵列特征值滤波方法的基础上,对特征值的进一步处理可以得到更好的去噪效果。 

Eigenvalue filtering method for microphone array denoising

Cross-Spectral Matrix(CSM),as a second-order statistic,is the critical input of an acoustic imaging algorithm.The mechanism of cross-spectral matrix eigenvalue filtering is investigated to enhance the performance of the microphone array.Two eigenvalue filtering methods are proposed:(1) The SURE-Shrinkage(Stein's Unbiased Risk Estimation) method of the cross-spectral matrix of sound sources;(2) The Opt-Shrinkage method,which is used to improve further the estimation results of EYM(Eckart-Young-Mirsky).Then,the simulation is carried out with the parameters of 3000 snapshots,0 dB Signal-to-Noise Ratio(SNR) and 100 microphones.The diagonal error of sound source CSM and de-noised CSM is used to compare the effectiveness of SURE and Opt-Shrinkage with the traditional Multi Signal Classification(MUSIC) method.The diagonal error of the MUSIC method is 74.15%,while the SUREShrinkage is 41.97%,and the Opt-Shrinkage is 20.62%.From the simulation results,under the condition of less than40 sound sources,the de-noising results of the SURE-Shrinkage are better than the MUSIC method and Opt-Shrinkage method;after the number of sound sources exceeds 42,the Opt-Shrinkage perform better.By changing the number of snapshots,the number of sound sources and SNR,the results of different eigenvalue filtering methods is compared.At last,in the experiment of sound source localization under three sources,60 microphones and-5 dB SNR condition,both SURE-Shrinkage and Opt-Shrinkage have a better de-noising performance compared with the MUSIC method.The research shows that better de-noising results can be obtained by further processing the eigenvalues.