'Institute of Electrical and Electronics Engineers (IEEE)'
Abstract
Data Driven Time Synchronization (DDTS) provides
synchronization across sensors by using underlying characteristics of data collected by an embedded sensing sys-
tem. We apply the concept of Data Driven Time Synchronization through a seismic deployment consisting
of 100 seismic sensors to repair data that was not time
synchronized correctly. This deployment used GPS for
time synchronization but due to system faults common
to environmental sensing systems, data was collected
with large time offsets. In seismic deployments, offset
data is often never used but we show that Data Driven
Time Synchronization can recover the synchronization
and make the data usable. To implement Data Driven
Time Synchronization to repair the time offsets we use
microseisms as the underlying characteristics. Microseisms are waves that travel through the earth’s crust
and are independent of the seismic events used for the
study of the earth’s structure. We have developed a
model of microseism propagation through a linear seismic array and use the model to obtain time correction
shifts. By simulating time offsets in real data which does
not have offsets, we determined that this method is able
to repair the offset to less than 0.2 seconds. Our ongoing work will attempt to refine the model to correct the
offsets to 0.05 seconds and evaluate how errors in the
correction affect seismic results such as event location.
Data Driven Time Synchronization may be applicable
to other high data rate embedded sensing applications
such as acoustic source localization