Abstract
A robust bearing estimation process for 3-component stations has been
developed and explored. The method, called SEEC for Search, Estimate,
Evaluate and Correct, intelligently exploits the inherent information
in the arrival at every step of the process to achieve near-optimal
results. In particular, the approach uses a consistent framework
to define the optimal time-frequency windows on which to make estimates,
to make the bearing estimates themselves, to construct metrics helpful
in choosing the better estimates or admitting that the bearing is
immeasurable, and finally to apply bias corrections when calibration
information is available to yield a single final estimate. The algorithm
was applied to a small but challenging set of events in a seismically
active region. It demonstrated remarkable utility by providing better
estimates and insights than previously available. Various monitoring
implications are noted from these findings.
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