Airborne infrared limb-viewing detectors may be used as surveillance sensors in order to detect dim military targets. These systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly on target detection probability. This background clutter, which results from small-scale fluctuations of temperature, density or pressure must therefore be analyzed and modeled.Few existing codes are able to model atmospheric structures and their impact on limb-observed radiance. SAMM-2 (SHARC-4 and MODTRAN4 Merged), the Air Force Research Laboratory (AFRL) background radiance code can be used to in order to predict the radiance fluctuation as a result of a normalized temperature fluctuation, as a function of the line-of-sight. Various realizations of cluttered backgrounds can then be computed, based on these transfer functions and on a stochastic temperature field.The existing SIG (SHARC Image Generator) code was designed to compute the cluttered background which would be observed from a space-based sensor. Unfortunately, this code was not able to compute accurate scenes as seen by an airborne sensor especially for lines-of-sight close to the horizon.Recently, we developed a new code called BRUTE3D and adapted to our configuration. This approach is based on a method originally developed in the SIG model. This BRUTE3D code makes use of a three-dimensional grid of temperature fluctuations and of the SAMM-2 transfer functions to synthesize an image of radiance fluctuations according to sensor characteristics. This paper details the working principles of the code and presents some output results. The effects of the small-scale temperature fluctuations on infrared limb radiance as seen by an airborne sensor are highlighted.
Airborne infrared limb-viewing sensors may be used as surveillance devices in order to detect dim military targets. These systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly on target detection probability. Consequently, the knowledge of the radiance small-scale angular fluctuations and their statistical properties is required to assess the sensors' detection capacity. In the stratosphere and in clear-sky conditions, the structured background is mainly due to inertia-gravity-wave and turbulence-induced temperature and density spatial fluctuations. Moreover, in the particular case of water vapor absorption bands, the mass fraction fluctuations play a non negligible role on the radiative field. Thereby, considering as a first approximation the temperature field and the water vapor field as stationary stochastic processes, the radiance autocorrelation function (ACF) can be expressed as a function of the temperature ACF and the water vapor mass fraction ACF. This paper presents the model developed to compute the two-dimensional radiance angular ACF. This model requires the absorption coefficients and their temperature derivatives, which were calculated by a line-by-line code dedicated to water vapor absorption bands. An analytical model was also developed for a simple homogeneous case, in order to validate the average values and the radiance fluctuation variance. The numerical model variance and variance distribution are also compared to SAMM2 outputs, the AFRL radiance structure computation code. The influence of water vapor fluctuations on radiance fluctuations is also discussed.
This paper presents the development of a Statistical Narrow Band model (SNB) in a nonequilibrium vibrational state for HCl and CO molecules. The population densities of the energy levels are obtained by a multi-temperature approach to compute nonequilibrium Line By Line (LBL) spectra. The SNB parameters are obtained by fitting the curves of growth from the LBL approach by a least squares error minimization using a Newton method for pure Lorentz and Doppler broadening regimes. The model is tested in Voigt broadening regime using a mixing rule and agrees well with the LBL approach. Finally, spectral correlation problems between η σ /κ σ and κ σ , where η σ and κ σ are the emission and absorption coefficients respectively, have been exhibited for CO 2 .
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