Detection Optimization of the Progressive Multi-Channel Correlation Algorithm Used in Infrasound Nuclear Treaty Monitoring
Abstract
This thesis develops methods to determine optimum detection thresholds for the Progressive Multi-Channel Correlation (PMCC) algorithm used by the International Data Centre (IDC) to perform infrasound 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 (P sub D) and the false alarm rate (FAR) at various consistency detection thresholds. Further, statistical detection theory via maximum a posteriori and Bayes cost approaches is used to determine station-level optimum "family" size thresholds of grouped detection "pixels" with similar signal attributes (i.e. trace velocity, azimuth, time of arrival, and frequency content) before the detection should be considered for network-level processing. Optimum family sizes are determined based upon the consistency threshold and filter configuration used to filter sensor data prior to running the detection algorithm. Finally, this research generates synthetic signals for particular array configurations, adjusts the signal-to-noise ratio (SNR) to determine the SNR failure levels for the PMCC detection algorithm, and compares this performance to the performance of fielded infrasound stations with similar configurations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2013
- Accession Number
- ADA590009
Entities
People
- Anthony M. Runco
Organizations
- Air Force Institute of Technology