1 March 2009 Worldwide assessments of laser radar tactical scenario performance variability for diverse low altitude atmospheric conditions at 1.0642 μm and 1.557 μm
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J. of Applied Remote Sensing, 3(1), 033521 (2009). doi:10.1117/1.3122349
Abstract
Spatial, spectral and temporal variations in operating conditions are major contributors to the expected variability/uncertainty in system performance. The ratio of signal-to-noise ratio (SNR) based on climatological data to a standard atmosphere is the primary performance metric used, with results presented in the form of histograms and maps of worldwide LADAR performance variation. This metric is assessed at 2 wavelengths, 1.0642 μm and 1.557 μm, for a number of widely dispersed land and maritime locations worldwide over oblique and vertical air to surface paths in which anticipated clear air aerosols and location specific heavy rain and 150 m thick fog occur. Seasonal, boundary layer, and time of day variations for a range of relative humidity percentiles are also considered. In addition to realistic vertical profiles of molecular and aerosol extinction, air-to-ground cloud free line of sight (CFLOS) probabilities as a function of location for this geometry are computed. Observations from the current study strongly indicate that use of the standard atmosphere to predict performance will produce overly optimistic, in many cases extremely so, estimates of expected performance. Locally heavy rain, when present, severely limits LADAR system performance at these wavelengths. Some operational capability exists for vertical looks through fog.
Steven T. Fiorino, Richard J. Bartell, Matthew J. Krizo, Daniel Fedyk, Kenneth Moore, Thomas Harris, Salvatore J. Cusumano, Richard D. Richmond, Matthew J. Gebhardt, "Worldwide assessments of laser radar tactical scenario performance variability for diverse low altitude atmospheric conditions at 1.0642 μm and 1.557 μm," Journal of Applied Remote Sensing 3(1), 033521 (1 March 2009). http://dx.doi.org/10.1117/1.3122349
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KEYWORDS
Aerosols

Climatology

Signal to noise ratio

Atmospheric particles

LIDAR

Atmospheric modeling

Humidity

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