HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Full Text (PDF) Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Arrowsmith, S. J. Articles by Hayward, C. Search for Related Content GeoRef GeoRef Citation

The F-Detector Revisited: An Improved Strategy for Signal Detection at Seismic and Infrasound Arrays

EES-17, Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, New Mexico 87545

Charles Katz

Science Applications International Corporation (SAIC), 10260 Campus Point Drive, San Diego, California 92121-1578

Chris Hayward

Department of Geological Sciences, Dedman College, Southern Methodist University, P.O. Box 750395, Dallas, Texas 75275

This short article explores and extends the adaptive detection algorithm recently developed by Arrowsmith, Whitaker, et al. (2008). In particular, this article highlights its application for seismic data, compares results for colocated seismic and infrasonic data, and assesses detector performance through comparison with analyst picks. We assess the adaptive detector by generating receiver-operating characteristic (ROC) curves, illustrating the trade-off between detection probability and false-alarm probability, and comparing the results with the conventional F-detector. The results show that the adaptive detector performs much better than the conventional detector for both seismic and infrasound data by maintaining high detection probabilities while significantly decreasing false-alarm probabilities, illustrating that correlated noise is ubiquitous for both types of data. The effect of the adaptation window is illustrated and shown to be especially important for infrasound data where diurnal variations in ambient noise levels are pronounced. A window choice of 1 hr (i.e., significantly less than 24 hr) is shown to be adequate for representing variations in ambient noise levels.