Automatic detection of martian seismic events using a single-component reduction algorithm
Abstract
We analyze the effectiveness of three STA/LTA-type automatic seismic event detection methods when applied to synthetic Martian seismograms in the framework of the Preparing for InSight project. The seismograms used correspond to a short-period, three- component velocity sensor. Due to the presence of significant ambient noise and other associated seismic events, the signal-to-noise ratio (S/N) of the data is considerably low. In this context, to improve the effectiveness of the detection methods, an algorithm is proposed to reduce the information contained in the three components of the seismogram to a single time series with a higher S/N ratio than that of each component separately. This also allows minimizing the computational cost and the ambiguities that could arise when performing the detection of each component separately. We analyze the effectiveness of the detection methods based on the number of correct detections obtained when using the reduced seismogram or the original seismograms separately. In addition, we compare the results with those obtained by other authors (Géoazur group) who used the same data. The comparison was first performed component by component, yielding a maximum coincidence of about 20 % with the events detected by the Géoazur group. This percentage rose to 30 % after applying the detection methods to the seismogram generated by the one-component reduction algorithm. These results represent a significant improvement in the effectiveness of the detection methods tested.
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