Using instantaneous phase coherence for signal extraction from ambient noise data at a local to a global scale
Using instantaneous phase coherence for signal extraction from ambient noise data at a local to a global scale
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DOI：
10.1111/j.1365-246x.2010.04861.x
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发表时间：
2011-01-01
影响因子：
2.8
通讯作者：
Gallart, J.
中科院分区：
文献类型：
--
作者：
Schimmel, M.;Stutzmann, E.;Gallart, J.
环境噪声互相关的堆栈越来越多地被用于提取站点对之间的经验格林函数。互相关的成功归功于由两个台站记录的波，并且以等于它们在台站对之间的传播时间的滞后时间建设性地求和。对应于不同时间跨度的叠加交叉相关图改善了方位向噪声覆盖，并进一步增强了信号。在这里，我们展示了如何使用瞬时相位相干性来从环境噪声互相关中更有效地提取信号。瞬时相位相干性是通过解析信号处理得到的，可以通过相位互相关和/或通过时频域相位加权叠加来实现。与传统的互相关法相比，相位互相关法对波形相似性更敏感，但对强幅度特征的敏感性较低。时频域相位加权叠加通过衰减非相干噪声来清除环境噪声交叉相关图，并允许改进信号识别。我们表明，这两种方法都是从环境噪声数据中恢复信号的强大工具，并展示了它们通过考虑局部和全球尺度的应用来改进P波和瑞利波提取的例子。
Stacks of ambient noise cross-correlations are more and more routinely used to extract empirical Green's functions between station pairs. The success of the cross-correlations is due to waves which are recorded by both stations and that constructively sum at lag times which equal their propagation time between the station pair. Stacking cross-correlograms corresponding to different time spans improves the azimuthal noise coverage and further enhances the signals. Here we show how the instantaneous phase coherence can be used for a more efficient signal extraction from ambient noise cross-correlations. The instantaneous phase coherence is obtained by analytic signal processing and can be employed through the phase cross-correlation and/or through the time-frequency domain phase-weighted stack. The phase cross-correlation is more sensitive to waveform similarity but less sensitive to strong amplitude features than the conventional cross-correlation. The time-frequency domain phase-weighted stack cleans the ambient noise cross-correlograms by attenuating incoherent noise and permits an improved signal identification. We show that both approaches are powerful tools in the recovery of signals from ambient noise data and show examples where they improve the extraction of P and Rayleigh waves by considering local and global scale applications.