基于Kalman滤波与频率聚焦的单声源到达方向实时估计与跟踪方法  

Real time estimation and tracking method for the direction of arrival of single sound source based on Kalman filtering and frequency focusing

作　　者：周静 鲍长春 段海威 ZHOU Jing;BAO Changchun;DUAN Haiwei(Institute of Speech and Audio Signal Processing,Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China)

机构地区：[1]北京工业大学信息学部,语音与音频信息处理研究所,北京100124

出　　处：《清华大学学报（自然科学版）》2024年第11期1902-1910,共9页Journal of Tsinghua University(Science and Technology)

基　　金：国家自然科学基金项目(61831019)。

摘　　要：为改善在噪声、混响及声源移动情况下传统到达方向(direction of arrival,DOA)估计方法的性能,该文提出一种基于Kalman滤波与频率聚焦的单声源DOA实时估计与跟踪方法。该方法由去噪、去混响和DOA估计3个步骤构成。其中:去噪与去混响步骤的目标函数分别由最小化去噪信号误差和多通道线性预测系数误差建立,并分别通过Kalman滤波求解;DOA估计步骤通过基于频率聚焦的导向响应功率实现。该文所提方法建立在传播矩阵集成去混响与去噪步骤的基础上,通过波束形成获得的期望信号的先验估计,DOA估计步骤被进一步集成,从而促进3个步骤间的因果有序迭代。实验结果表明:与参考方法相比,该文所提方法的DOA估计与跟踪性能更优。[Objective] Estimation of direction of arrival(DOA) is critical in spatial audio coding,speech enhancement,sound field synthesis,and sound source imaging.Commonly used signal model-based DOA estimation methods,such as the multiple signal classification method,can effectively estimate DOA information in noise-free and anechoic scenarios.However,real-world environments always have noise and reverberation,particularly in far-field speech communication scenarios characterized by low signal-to-noise ratios and strong reverberation.Furthermore,the sound source may be in motion.These factors considerably impair the performance of DOA estimation methods based on signal models.To address this issue,this paper introduces a real-time estimation and tracking method for the DOA of a single sound source,using Kalman filtering and frequency focusing.[Methods] The proposed method consists of three procedures:denoising,dereverberation,and DOA estimation.With regard to the denoising procedure,an objective optimization function to minimize the error of the denoised signal is established.This function is solved using a Kalman filter,which leads to obtaining the denoised signal through Kalman gain-based posterior estimation.For the dereverberation procedure,based on the autoregressive coefficients of the late reverberation components,an objective optimization function to minimize the error of the multichannel linear prediction(MCLP) coefficients is established.This function is also solved through another Kalman filter to obtain the MCLP coefficients.The DOA estimation procedure is implemented by using a frequency focusing based steered response power(FF-SRP) method,which can circumvent signal component diffusion within subspace decomposition.In particular,a structure that effectively intertwines these three procedures,enhancing the contribution of denoising and dereverberation results to DOA estimation.In this structure,a propagation matrix is utilized to integrate the denoising and dereverberation procedures,creating a causative ite

关 键 词：到达方向估计 多通道线性预测 KALMAN滤波 频率聚焦 去混响 

分 类 号：TP912.3[自动化与计算机技术]