Optimizing the PMCC Algorithm for Infrasound and Seismic Nuclear Treaty Monitoring

Abstract

We introduce novel methods to determine optimum detection thresholds for the Progressive Multi-Channel Correlation (PMCC) algorithm used by the International Data Centre (IDC) to perform infrasound and seismic station-level nuclear-event detection. Receiver Operating Characteristic (ROC) curve analysis is used with real ground truth data to determine the trade-off between the probability of detection and the false alarm rate (FAR) at various detection thresholds. Further, statistical detection theory via maximum a posteriori and Bayes cost approaches is used to determine station-level optimum “family” size thresholds before detections should be considered for network-level processing. These threshold-determining methods are extensible for family-characterizing statistics other than “size,” such as a family’s collective F-statistic or signal-to-noise ratio (SNR). Therefore, the reliability of analysts’ decisions as to whether families should be preserved for network-level processing can only benefit from access to multiple, independent, optimum decision thresholds based upon size, F-statistic, SNR, etc.