The detection and location capability of the International Monitoring System for small seismic events in the continental and oceanic regions surrounding the Sea of Japan is determined mainly by three primary seismic arrays: USRK, KSRS, and MJAR. Body wave arrivals are coherent on USRK and KSRS up to frequencies of around 4 Hz and classical array processing methods can detect and extract features for most regional signals on these stations. We demonstrate how empirical matched field processing (EMFP), a generalization of frequency-wavenumber or f-k analysis, can contribute to calibrated direction estimates which mitigate bias resulting from near-station geological structure. It does this by comparing the narrowband phase shifts between the signals on different sensors, observed at a given time, with corresponding measurements on signals from historical seismic events. The EMFP detection statistic is usually evaluated as a function of source location rather than slowness space and the size of the geographical footprint valid for EMFP templates is affected by array geometry, the available

signal bandwidth, and Earth structure over the propagation path. The MJAR arrayhas similar dimensions to KSRS but is sited in far more complex geology which results in poor parameter estimates with classical f-k analysis for all signals lacking energy at 1 Hz or below. EMFP mitigates the signal incoherence to some degree but the geographical footprint valid for a given matched field template on MJAR is very small. Spectrogram beamforming provides a robust detection algorithm for high-frequency signals at MJAR. The array aperture is large enough that f-k analysis performed on continuous AR-AIC functions, calculated from optimally bandpass-filtered signals at the different sites, can provide robust slowness estimates for regional P-waves. Given a significantly higher SNR for regional S-phases on the horizontal components of the 3-component site of MJAR, we would expect incoherent detection and estimation of S-phases to improve with 3-component sensors at all sites. Given the diversity of the IMS stations, and the diversity of the methods which provide optimal results for a given station, we advocate the development of seismic processing pipelines which can process highly heterogeneous inputs to help associate characteristics of the incoming signals with physical events.

国际监测系统对日本海周边大陆和海洋区域小地震事件的检测和定位能力主要由三个主要地震阵列决定：USRK、KSRS 和 MJAR。体波到达在 USRK 和 KSRS 上是相干的，频率高达 4 Hz 左右，经典的阵列处理方法可以检测和提取这些台站上大多数区域信号的特征。我们展示了经验匹配场处理 (EMFP)，频率-波数或 fk 分析的概括，如何有助于校准方向估计，从而减轻近站地质结构造成的偏差。它通过比较在给定时间观察到的不同传感器上的信号之间的窄带相移来实现这一点，对来自历史地震事件的信号进行相应的测量。EMFP 检测统计通常被评估为源位置而不是慢度空间的函数，并且对 EMFP 模板有效的地理足迹的大小受阵列几何形状的影响，可用的

信号带宽和传播路径上的地球结构。MJAR 阵列具有与 KSRS 相似的尺寸，但位于更复杂的地质环境中，这导致对所有缺乏 1 Hz 或以下能量的信号的经典 fk 分析的参数估计较差。EMFP 在一定程度上减轻了信号的不相干性，但对于 MJAR 上给定的匹配字段模板有效的地理足迹非常小。频谱图波束成形为 MJAR 的高频信号提供了一种稳健的检测算法。阵列孔径足够大，以至于对连续 AR-AIC 函数执行的 fk 分析（根据不同站点的最佳带通滤波信号计算）可以为区域 P 波提供稳健的慢度估计。鉴于 MJAR 的 3 分量站点的水平分量上区域 S 相的 SNR 显着更高，我们预计 S 相的非相干检测和估计将在所有站点上使用 3 分量传感器得到改善。鉴于 IMS 台站的多样性，以及为给定台站提供最佳结果的方法的多样性，我们提倡开发地震处理管道，该管道可以处理高度异构的输入，以帮助将传入信号的特征与物理事件相关联。