Characterizing Footstep Detection Thresholds with Distributed Acoustic Sensing

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Abstract The resolution of distributed acoustic sensing (DAS) has allowed researchers to detect and analyze a wide variety of seismic and nonseismic sources, such as humans walking. Using preinstalled DAS fibers in telecommunication conduits near human communities makes detecting footstep sources nearly unavoidable. Researchers in the environmental and urban seismology fields see such anthropogenic sources as their signals of interest. However, traditional seismologists may view them as undesirable noise. Targeting or removing such sources requires an understanding of their characteristics. Previous research focused on recording walking signals has demonstrated DAS’s ability to record individual footsteps along a continuous path. Yet, most studies have used footsteps falling immediately above the fiber, with walking paths running parallel to the fiber. Those works provided valuable information on how footstep wavefields propagate. However, previous researchers have not addressed how far away DAS can detect a footstep. Many seismologists use preinstalled DAS with little or no control over array location. Thus, the wider community would benefit from a better understanding of off-fiber footstep detectability. Here, we use wavefields generated by a person walking recorded by a DAS array to locate footsteps through space and time. The footsteps are modeled as a series of discrete impulse forces which are located with backprojection. We explain the recorded amplitudes of a fiber-oblique walking path using a seismic impact model and wave propagation theory. Using this model and the observed amplitudes, we estimate an empirical site-specific maximum footstep detection threshold distance of ≤24 m that is valid for alluvial sites. This threshold can guide researchers in finding ideal DAS array settings, whether they seek to record footstep wavefields or avoid them.