A new method of simultaneous time domain cross-correlation of multiple components of motion at multiple seismic stations is developed for P- and S-wave identification for determination of arrival times of deep moonquakes using Apollo Passive Seismic Experiment (APSE) data. Deep moonquakes occur in selenographically isolated clusters, allowing the stacking of a large number of moonquakes in each cluster to improve signal-to-noise ratio. The method developed here seeks to improve upon multichannel cross-correlation (MCCC) of a single component of motion and multiple events used in past work by incorporating all components and stations simultaneously. This multicomponent multichannel cross-correlation (MCMCCC) method not only maximizes the inherent correlation between the 12 components (three components of motion at each of four stations) across all events in a given cluster, but also establishes representative stacked traces of moonquakes within each cluster. Additionally, the MCMCCC method utilizes components and events with the highest data quality to guide the inclusion of lower quality components and events (or events with fewer components). A closure difference residual time is introduced to identify moonquake events with better data and/or close source locations, to further improve the signal-to-noise ratio of stacked traces. A multicomponent short-term to long-term average algorithm is also developed to objectively determine P- and S-wave arrivals that best align with their travel time curves based on lunar velocity models, simultaneously for all 12 components of motion. Newly computed deep moonquake cluster stacks and some updated deep moonquake cluster locations are presented, which improve upon past results.
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