Multiple Aerosol Unmixing by the Split Bregman Algorithm

Abstract

For more than a decade the US government has been developing laser-based sensors for detecting, locating, and classifying aerosols in the atmosphere at safe standoff ranges. The motivation for this work is the need to discriminate aerosols of biological origin from interferent materials such as smoke and dust using the backscatter from multiple wavelengths in the long-range IR (LWIR) spectral region. Through previous work, algorithms have been developed for estimating the aerosol spectral dependence and concentration range-dependence from these data. The range-dependence is required for locating and tracking the aerosol plumes, and the backscatter spectral dependence is used for discrimination by a support vector machine classifier. Substantial progress has been made in these algorithms for the case of a single aerosol present in the lidar line-of-sight (LOS).

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2011
Accession Number
ADA555738

Entities

People

  • Richard Vanderbeek
  • Russell Warren
  • Stanley Osher

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Atmospheres
  • Backscattering
  • Biological Aerosols
  • Computer Science
  • Data Analysis
  • Detection
  • Fungi
  • Inverse Problems
  • Line Of Sight
  • Long-Wavelength Infrared Radiation
  • Machine Learning
  • Materials
  • Mathematics
  • Standoff
  • Supervised Machine Learning

Fields of Study

  • Physics

Readers

  • Aerosol Science/Aerosol Physics
  • Image Processing and Computer Vision.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • Directed Energy