Statistical Framework for Event Identification and Assessment of Seismic CTBT Monitoring Capability,
Abstract
This effort focuses on several main areas regarding event identification within the context of CTBT monitoring: (1) development and integration at the Center for Monitoring Research (CMR) of a software system for event characterization/identification; (2) assessment of regional seismic event identification performance; (3) analysis of GSETT-3 Alpha network data to assess the availability and utility of event characterization parameters for global monitoring; and (4) investigation of robust multi-sensor data fusion techniques for outlier detection and event classification. We have been implementing a statistical event identification framework. The fundamental methods consist of statistical tests for outlier detection and event classification, as well as algorithms to test appropriate assumptions regarding the data in order to optimize and ensure validity of the results. Our methodology: (1) accurately treats statistical uncertainties of all discriminants used; (2) provides flexibility to incorporate any discriminant and assess its utility objectively; (3) can identify nuclear tests in regions for which relevant ground-truth training data may or may not exist; (4) can function in an automated mode to flag, categorize and/or rank anomalous events; (5) can control the false alarm rate; (6) and provides a rigorous and defensible framework with which to report and justify the results. To also serve as an interactive analysis tool, we have been developing an X Window graphical user interface, featuring a wide range of displays and exploratory data analysis tools. We have applied the methods to seismic events recorded by the ARCESS and GERESS arrays, station WMQ in China, and stations KNB and MNV in the western U.S.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 14, 1995
- Accession Number
- ADP204505
Entities
People
- Gary D. Mccartor
- Henry L. Gray
- Mark D. Fisk