RUSSIAN JOURNAL OF EARTH SCIENCES, VOL. 19, ES2001, doi:10.2205/2018ES000649, 2019

Table 1. Input Parameters Used for Testing of the Proposed Algorithm
$\Delta f$, Hz 6–16 LAG, s 60
STA, s 1 PER 4
LTA, s 30 STAenv, s 0.2
Threshold value 10 LTAenv, s 30
CoincIndex 2 SpikesLen, s 5

Note: $\Delta f$ – frequency band of the digital filter; STA – length of the moving short-term window in STA/LTA block; LTA – length of the moving long-term window in STA/LTA block; Threshold value – triggering threshold for STA/LTA ratio; CoincIndex – minimum number of stations for making positive consistency decision; LAG – accepted time span for the block of consistency check; PER – minimum number of trigger alarms with almost equal intervals in order to classify the signal as produced by engineering works; STAenv – length of moving short-term window in signal duration block; LTAenv – length of moving long-term window in signal duration block; SpikesLen – maximum duration of the envelope ($C>0$) to be assigned to the microquakes.

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Citation: Krylov A. A., L. I. Lobkovsky, A. I. Ivashchenko (2019), Automated detection of microearthquakes in continuous noisy records produced by local ocean bottom seismographs or coastal networks, Russ. J. Earth Sci., 19, ES2001, doi:10.2205/2018ES000649.
 

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