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.