Enhancements to the Bayesian Infrasound Source Location Method

Abstract

We report on R&D that is enabling enhancements to the Bayesian Infrasound Source Location (BISL) method for infrasound event location. The focus of this effort is on improving BISL through the development and implementation of physics-based priors. Phase identification in BISL is incorporated through a prior probability density function on group velocity. We report on the development of a distance-dependent prior through a massive simulation effort that will be validated by a ground-truth data analysis effort. In addition to providing constraints for the prior Probability Density Function (PDF), this coupled effort is also providing constraints on the probability distributions that are used in the likelihood equations in BISL. We assess the enhancement in location precision using a dynamic prior, instead of the previous uniform prior, for some example events. Finally, we discuss efforts to improve the numerical implementation of BISL using Monte Carlo integration.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2012
Accession Number
ADA570041

Entities

People

  • Dale N. Anderson
  • Omar E. Marcillo
  • Rod W. Whitaker
  • Stephen J. Arrowsmith

Organizations

  • Los Alamos National Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Data Analysis
  • Data Science
  • Explosions
  • Ground Based
  • Group Velocity
  • Information Science
  • Infrasounds
  • Monitoring
  • Monte Carlo Method
  • Nuclear Explosions
  • Precision
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Simulations

Readers

  • Computational Modeling and Simulation
  • Statistical inference.
  • Superconducting Magnet Technology

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference