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Shallow seismic sources excite Rayleigh wave ground motion with azimuthallydependent radiation patterns. We place binary hypothesis tests on theoreticalmodels of such radiation patterns to screen cylindrically symmetric sources(like explosions) from non-symmetric sources (like non-vertical dip-slip, ornon-VDS faults). These models for data include sources with several unknownparameters, contaminated by Gaussian noise and embedded in a layeredhalf-space. The generalized maximum likelihood ratio tests that we derive fromthese data models produce screening statistics and decision rules that dependon measured, noisy ground motion at discrete sensor locations. We explicitlyquantify how the screening power of these statistics increase with the size ofany dip-slip and strike-slip components of the source, relative to noise(faulting signal strength), and how they vary with network geometry. Asapplications of our theory, we apply these tests to (1) find optimal sensorlocations that maximize the probability of screening non-circular radiationpatterns, and (2) invert for the largest non-VDS faulting signal that could bemistakenly attributed to an explosion with damage, at a particular attributionprobability. Lastly, we quantify how certain errors that are sourced by openingcracks increase screening rate errors. While such theoretical solutions areideal and require future validation, they remain important in undergroundexplosion monitoring scenarios because they provide fundamental physical limitson the discrimination power of tests that screen explosive from non-VDSfaulting sources.

Hypothesis Tests on Rayleigh Wave Radiation Pattern Shapes: A Theoretical Assessment of Idealized Source Screening