Single Station Triaxial Seismic Event Detection, Direction Finding and Polarization Analysis

S. Greenhalgh, A. Al-Lehyani, C. Schmelzbach, D. Sollberger
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Abstract

The bearing and elevation (azimuth and inclination) of a seismic event can be estimated directly from measurements at a single triaxial station. There are instances in which the angular resolution secured by triaxial polarization analysis is better than that obtained by beamforming with an extended scalar array. In these situations, one depends totally on understanding the inter-relationships between the triaxial records that make up a seismic wavetrain. There are many approaches to seismic direction finding (SDF). Monte-Carlo techniques of triaxial seismic direction finding seek to maximise signal power by examining the seismic wavefield in many rotated co-ordinate frames. There are variants on this approach, which entail null seeking in an inverse space. Instead of searching all possible directions for the one which best fits the polarization model of a single arrival, it is possible to carry out an eigen-decomposition of the (complex or real) covariance matrix formed from the three-component data. The eigenvector corresponding to the principal eigenvalue yields the polarization direction automatically, with significant savings in computational effort. Numerical experiments undertaken for different levels of random noise superimposed on a pure mode signal show that there are no significant advantages in using the Monte-Carlo techniques over eigendecompsoition. Confidence measures of event detection may be obtained by examining eigenvalue ratios when using the eigendecompsoition method. A time-domain formulation (covariance or coherency matrix) is preferable to a frequency-domain formulation (cross-spectral matrix) when there are multiple transient events present. The analysis window should be as long as possible (at least half the dominant period of the signal) without causing separate events to interfere. In practise, the direction-of-arrival estimates deteriorate with increasing levels of random noise, and are generally unacceptable for a SNR of less than 1. Special care is needed to avoid direction errors associated with systematic noise, such as sensor gain misalignment between channels, coupling variations between receiver components, velocity inhomogeneity and anisotropy, the free-surface effect, and multiple event interference.
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单站三轴地震事件探测、测向和极化分析
地震事件的方位和仰角(方位角和倾角)可以直接从单个三轴站的测量中估计出来。在某些情况下,三轴极化分析获得的角分辨率优于扩展标量阵列波束形成获得的角分辨率。在这些情况下,人们完全依赖于理解构成地震波列的三轴记录之间的相互关系。地震测向(SDF)有许多方法。蒙特卡罗三轴地震测向技术试图通过在许多旋转坐标系中检查地震波场来最大化信号功率。这种方法有多种变体,它们需要在逆空间中寻找零。代替搜索所有可能的方向来寻找最适合单一到达的极化模型的方向,可以对由三分量数据形成的(复或实)协方差矩阵进行特征分解。与主特征值相对应的特征向量自动产生极化方向,大大节省了计算量。对叠加在纯模信号上的不同水平的随机噪声进行的数值实验表明,与特征分解相比,使用蒙特卡罗技术没有明显的优势。当使用特征分解方法时,可以通过检查特征值比率来获得事件检测的置信度度量。当存在多个瞬态事件时,时域公式(协方差或相干矩阵)优于频域公式(交叉谱矩阵)。分析窗口应尽可能长(至少是信号主导周期的一半),而不引起单独事件的干扰。在实践中,到达方向估计随着随机噪声水平的增加而恶化,并且对于小于1的信噪比通常是不可接受的。需要特别注意避免与系统噪声相关的方向误差,例如通道之间的传感器增益不对准、接收器组件之间的耦合变化、速度不均匀性和各向异性、自由面效应和多事件干扰。
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