| Summary: | It has long been accepted that occurrences of a known signal are most effectively detected by cross-correlating the incoming data stream with a waveform template. Such matched signal detectors have received very little attention in the field of detection seismology because there are relatively few instances in which the form of an anticipated seismic signal is known a priori. Repeating events in highly confined geographical regions have been observed to produce very similar waveforms and good signals from events at a given site can be exploited to detect subsequent co-located events at lower magnitudes than would be possible using traditional power detectors. Even greater improvement in signal detectability can be achieved using seismic arrays; running correlation coefficients from single sensors can be stacked over an array or network to result in a network correlation coefficient displaying a significant array gain. If two events are co-located, the time separating the corresponding patterns in the wave train as indicated by the cross-correlation function is identical for all seismic stations and this property means that the correlation coefficient traces are coherent even when the waveforms are not. We illustrate the power of array-based waveform correlation using the 1997 August 16 Kara Sea event. The weak event that occurred 4 hr after the main event was barely detected using an STA/LTA detector on the SPITS array but is readily detected by signal matching on a single channel. The main event was also recorded by the far more distant NORSAR array but no conventional detection can be made for the second event. A clear detection is, however, made when the correlation coefficient traces are beamformed over all sensors of the array. We estimate the reduction in detection threshold of a test signal on a regional seismic array using waveform correlation by scaling down a master signal and immersing it into seismic noise. We show that, for this case, waveform correlation using a single channel detects signals of ...
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