基于小波分析的广义互相关时延估计研究

2011 First International Conference on Instrumentation, Measurement, Computer, Communication and Control Pub Date : 2011-10-21 DOI:10.1109/IMCCC.2011.28

Wang Hongkai, Fan Liqing, Xiong Chao

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引用次数: 2

摘要

由于广义互相关算法在延迟算法中具有较高的实时性，当实验环境是先验可知时，通常采用广义互相关算法。广义互相关方法的预滤波对时延估计的精度影响较大，针对如何在兼顾精度的情况下实时有效地利用广义互相关方法的问题，本文提出了基于小波分析的广义互相关算法。不同的麦克风接收相同的声音信号，信号的基本特征是相同的。小波变换可以有效地增强声信号的基本特征，提高广义互相关方法的精度。仿真结果表明，基于小波分析的广义互相关算法具有较好的精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Research of Generalized Cross Correlation to Time Delay Estimation Based on Wavelet Analysis

As the generalized cross-correlation method has high real-time in the delay Algorithm, when the experiment environment is the a priori knowable, Generalized cross-correlation algorithm is usually used. The pre-filtering of the generalized cross-correlation method has a greater impact on the accuracy of time delay estimation, for the problem that how to effectively use the generalized cross-correlation method in real time taking the accuracy into account, proposed generalized cross correlation algorithm based on wavelet analysis in this paper. Receiving the same sound signals for different microphones, the basic features of the signal is the same. Wavelet transform can effectively strengthen the basic features of the acoustic signal, and improve the accuracy of the generalized cross correlation method. The simulation shows that the generalized cross correlation algorithm based on wavelet analysis has good accuracy.

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来源期刊

2011 First International Conference on Instrumentation, Measurement, Computer, Communication and Control

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