Validation/Evaluation of Polarization Version of SEARAD Model

Abstract

Until recently no standard atmospheric propagation codes included the effects of polarization. Recently a research grade upgrade to MODTRAN (Zeisse, Nrad) has allowed the polarized case. This upgrade, called SEARAD, calculates the infrared polarization of sea surface radiance. Data available in the EOPACE data base were used for a direct comparison of the code prediction to the measurements. The data consist of polarized and unpolarized images of the R/V POINT SUR in the Long Wave Infrared (LWIR), taken with the AGA 780 camera during an experiment conducted in San Diego Bay in April 1996. Meteorological, geographical, and external ship temperature data were recorded along with the images. The analysis of the EOPACE data was conducted by using IDL (Interactive Data Language) analysis programs and included 34 sets of images. The sea pixels were extracted from the images, and correlated with meteorological, and geographical data to provide input to the SEARAD code. The comparison of the experimental data with the SEARAD predictions yielded an average error of 1.57/sq Wm/sr in unpolarized sea radiance, which is within approximately 5% of the experimental radiance, and an average 0.51 absolute difference between the predicted and experimental degree percentage of polarization.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1999
Accession Number
ADA365669

Entities

People

  • Panagiotis Karavas

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Atmospheric Attenuation
  • Computers
  • Data Analysis
  • Databases
  • Detection
  • Detectors
  • Electromagnetic Spectra
  • Experimental Data
  • Flux Density
  • Infrared Radiation
  • Language
  • Long-Wavelength Infrared Radiation
  • Measurement
  • Operating Systems
  • Optics
  • Radiation
  • Scattering

Readers

  • Atmospheric Remote Sensing.
  • Computer Science.