Lidar Observations at 0.7 Micrometer and 10.6 Micrometer Wavelengths during Dusty Infrared Test I (DIRT-I). Additional Results.

Abstract

The Dusty Infrared Test I (DIRT-I) was held at White Sands Missile Range (WSMR) in October 1978 to evaluate various techniques to measure physical and optical properties of battlefield dust. Since lidar technique represents one of the most promising techniques, two lidar systems: 10.6 micrometer wavelength (ASL-lidar) and 0.7 micrometer Ruby lidar system (Mark IX), were operated over a common 2-km optical path during this test. Primary lidar backscatter data for both wavelengths were recorded on magnetic tape by using Mark IX lidar data system while independent 10.6 micrometer lidar transmission data were recorded on strip chart in the ASL lidar van. Photographs were also taken every 30 to 60 seconds during each event of range-resolved 10.6 micrometer backscatter amplitude data (A-Scope presentation). Results of the DIRT-I program indicate that the broad particle size distribution present in the dust generated at White Sands produces little if any wavelength-dependent transmission effects. The few observed exceptions, where greater 10.6 micrometer transmission is indicated, generally can be explained by the presence of wavelength-dependent smoke (which was also generated by the detonations) along the optical path.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1980
Accession Number
ADA103377

Entities

People

  • J. S. Randhawa

Organizations

  • Atmospheric Sciences Laboratory

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Artillery
  • Artillery Ammunition
  • Atmospheric Sciences
  • Backscattering
  • Classification
  • Detectors
  • Display Systems
  • Electronics
  • Magnetic Tape
  • Measurement
  • Observation
  • Optical Properties
  • Particle Size
  • Plastic Explosives
  • Quantum Electronics
  • Tapes
  • Video Tapes

Fields of Study

  • Physics

Readers

  • Atmospheric Remote Sensing.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Spectroscopy.