Detection and Characterization of Chemical Vapor Fugitive Emissions from Hyperspectral Infrared Imagery by Nonlinear Optimal Estimation

Abstract

Algorithm Development: Overview * Objectives * Improve pixel-level detection: Reduce probability of false alarm for given Pd * Address optically-thick plumes: Improve accuracy of estimated path integrated concentration (column density, CL) * Compatible with real-time processing * Limitations of current practice * Matched-filter-based detection presumes optically-thin plume * Other approaches require prior measurements of background - not compatible with on-the-move detection * Payoff: Improve detection immediately following large-scale release, low-lying plumes; improve mass estimate.

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Document Details

Document Type
Technical Report
Publication Date
Apr 09, 2010
Accession Number
ADA522526

Entities

People

  • Christopher M. Gittins

Organizations

  • Physical Sciences (United States)

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Covariance
  • Data Acquisition
  • Data Processing
  • Detection
  • Detectors
  • Emission
  • Estimators
  • False Alarms
  • Matched Filters
  • Measurement
  • Models
  • Physical Sciences
  • Radiative Transfer
  • Statistics
  • Warning Systems

Readers

  • Aerosol Science/Aerosol Physics
  • Computer Vision.
  • Systems Analysis and Design