| AbstractDigital algorithms
for robust detection of phase arrivals in the presence of stationary and
nonstationary noise have a long history in seismology and have been
exploited primarily to reduce the amount of data recorded by data
logging systems to manageable levels. In the present era of inexpensive
digital storage, however, such algorithms are increasingly being used to
flag signal segments in continuously recorded digital data streams for
subsequent processing by automatic and/or expert interpretation systems.
In the course of our development of an automated, near-real-time,
waveform correlation event-detection and location system (WCEDS), we
have surveyed the abilities of such algorithms to enhance seismic phase
arrivals in teleseismic data streams. Specifically, we have considered
envelopes generated by energy transient (STA/LTA), Z-statistic,
frequency transient, and polarization algorithms. The WCEDS system
requires a set of input data streams that have a smooth, low-amplitude
response to background noise and seismic coda and that contain peaks at
times corresponding to phase arrivals. The algorithm used to generate
these input streams from raw seismograms must perform well under a wide
range of source, path, receiver, and noise scenarios. Present
computational capabilities allow the application of considerably more
robust algorithms than have been historically used in real time.
However, highly complex calculations can still be computationally
prohibitive for current workstations when the number of data streams
become large. While no algorithm was clearly optimal under all source,
receiver, path, and noise conditions tested, an STA/LTA algorithm
incorporating adaptive window lengths controlled by nonstationary
seismogram spectral characteristics was found to provide an output that
best met the requirements of a global correlation-based event-detection
and location system.Return to Table
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