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

机译:基于小波分析的延时估计广义互相关研究

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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.
机译:随着广义的互相关方法在延迟算法中具有高实时的,当实验环境是先验明显的,通常使用广义互相关算法。广义互相关方法的预滤波对时间延迟估计的准确性产生了更大的影响,对于如何在实时使用广义互相关方法的问题考虑到准确性,所提出的广义交叉相关性基于本文小波分析的算法。接收不同麦克风的相同声音信号,信号的基本功能是相同的。小波变换可以有效地增强声学信号的基本特征,提高了广义交叉相关方法的准确性。仿真表明,基于小波分析的广义互相关算法具有良好的精度。

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