摘要：BackgroundA GPS/acoustic (GPS/A) geodetic observation technique allows us to determine far offshore plate motion in order to understand the mechanism of megathrust earthquakes.In this technique, the distance between a sea-surface platform and seafloor transponders is estimated using the two-way traveltimes (TWT) of acoustic signals.TWTs are determined by maximizing the cross-correlation coefficient between the transmitted and returned signals.However, this analysis caused significantly wrong detection of TWT when the correlogram has an enlarged secondary envelope due to the enlarged amplitude of multiple signals depending on the relative spatial geometry between the ship and the transponder.The handled manual rereading of thousands of correlograms to obtain correct TWTs needs enormous time, and human errors may cause.To prevent these difficulties, an automated TWT determination procedure is valid to process numerous GPS/A data efficiently not only without human errors but also with high precision.Proposed methodsWe developed automated methods for precisely analyzing GPS/A data.Method 1: The maximum peak in the observed correlogram is read, and a synthetic correlogram is then subtracted from the observation.Then, the same operation is applied to the subtracted waveform.This procedure is iterated until the correlation coefficient lowers than a pre-defined threshold.A true traveltime is defined as the fastest traveltime during the iterations.Method 2: The observed correlograms are divided into several groups based on their similarity through cluster analysis, and a master waveform in each group is selected.Then, the traveltime residual between the maximum and true peaks in the master waveform is manually evaluated.The obtained residual is employed as the correction value for each slave waveform.Further, we employed a seismic data projection to visually inspect the reliability of obtained results.ResultsWe confirmed that both new methods accurately correct misreadings in the current method, which amount to 0.4–0.8 ms roughly corresponding to 30–60 cm difference in the slant range.ConclusionsThus, the proposed algorithms significantly improve the estimation of the transponder location.Further analyses are required to determine the arbitrary threshold values and to construct fully automated algorithms.
