Modeling of polarized radiances in the visible through IR regions requires consistent models for reflectance and emittance of materials. These models must include common effects such as directionality and spectral shape. We have started from a well validated but non-polarized Bi- Directional Reflectance Distribution Function/Directional Emittance model and have added in the polarization state description via Fresnel scaling. The methodology is discussed along with our approach to dealing with possible inconsistencies. Results are demonstrated within a complete 3D polarized object model.
The prediction of infrared emissions from gaseous plumes is an important tool for remote sensing, heat transfer, and vulnerability assessment. We have developed a software model called 'RAD3D'that generates hyperspectral images of 3D gaseous plumes. The model directly ray-traces through gas volumes input in the PLOT3D format. In addition to single and arrays of lines of sight, the model will automatically generate additional lines of sight to resolve image structure. Outputs of the model include hyperspectral and in-band radiances and transmittances, along with range-to-plume images. Opaque body regions may be embedded within the gas volume.
Hyperspectral and multispectral imagery provide a powerful remote sensing tool. In applications for which the image is produced by gaseous emission, analysis of the image to obtain the concentration and temperature of the gas flow is difficult and computationally intensive. We have developed a solution to this analysis problem using a physics-based scene model coupled with an automatic solver, a nonlinear optimization algorithm. The image set is modeled using a parameterized description of the gaseous flowfield and a three-dimensional spectral gas radiance model. The solver algorithm generates a trial flowfield and runs the radiance model, iteratively varying the flow parameters until an optimum match is obtained between measured and modeled images. An example analysis is shown using multispectral images of a microgravity flame.
The augmentation of passive IR conventional and hyperspectral imaging sensors with polarimetric capability offers enhanced discrimination of man-made and geophysical targets, along with inference of surface shape and orientation. In our efforts to size the design of IR polarimetric hyperspectral imagers to various remote discrimination applications, we have ascertained critical relationships between polarimetric SNR and pixel sizing. This relationship pertains primarily to realms wherein the objects to be sensed will be marginally resolved spatially. The determination of such application- specific relationships is key to the design of effective polarimetric sensors. To quantify this key trade-off relationship, we have employed the latest developmental version of SPIRITS, a detailed physics-based signature code which accounts for the various geometric, environmental illumination, and propagation effects. For complex target shapes, detailed accounting for such effects is especially crucial to accurate prediction of polarimetric signatures, and thus precludes hand calculation for all but simple uniformly planar objects. Key to accurate polarimetric attribute prediction is our augmentation of the Sandford-Robertson BRDF model to a Mueller/Stokes formalism that encompasses representation of fully general elliptically polarized reflections and linearly polarized thermal emissions in strict compliance with Kirchoff's Law. We discuss details of the polarimetric augmentation of the BRDF and present polarimetric discriminability-resolution trade-off results for various viewing aspects against a ground vehicle viewed from overhead.
The occurrence of background clutter is an on-going issue in the development of electro- optical sensors and seekers. Clutter varies with many parameters, which makes it costly to utilize measured data. Modeled backgrounds must be tested, however, to determine if the clutter they generate is realistic. The study reported here was performed with several goals: (1) to develop a methodology for studying clutter; (2) to compare the clutter levels from different scene elements; (3) study variations in spectral bandpass and in atmospheric visibility; and, (4) to study the effect of varying model sophistication on clutter. The last goal is one which has not previously been studied, to our knowledge. These results give model developers guidance on what model elements deserve the most resources. The present study focused on a generic reticle seeker, such as would be used in a tactical missile. The backgrounds studied were of tree-lines horizons, sun-heated rocks, and broken clouds, in four spectral bands within the 1 to 12 micron infrared region. Atmospheric haze levels were varied from 1 km to 23 km visibility. For these computations, the order of importance to clutter levels was, (1) scene type, (2) model sophistication level, and (3) haze. Strong variations with spectral band were also noted, although bands could not be compared fairly.
A new spectrally precise approach to Schumann-Runge synthesis has been devised, employing nine (9) different spectral arrays containing polynomial coefficients. The coefficients were fit to calculated cross sections obtained from a detailed Schumann-Runge model that incorporates the most recent high resolution spectroscopic data for a temperature range between 130 and 500K. This large data base is being used to reexamine the existing parameterizations of UV transmission and photolysis. In addition, it is now possible to extend atmospheric radiance codes further into the ultraviolet. Initial implementation has been accomplished for the MODTRAN code as part of the eventual development of AURIC, the Atmospheric Ultraviolet Radiance Integrated Code.
The U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) is administering a multi-year, multi-agency infrared background data and modeling program entitled Smart Weapons Operability Enhancement (SWOE). This paper describes the progress made to date in model development and integration, under the direction of the Geophysics Directorate of the Air Force Phillips Laboratory. Other aspects of the program, not described here, include measurements and database development. A 1-D thermal model for natural backgrounds has been developed that covers a full range of background types. The range of types includes vegetated and nonvegetated surfaces, winter conditions, porous materials, and the presence of soil moisture. The model is also being used as a test bed for the development of a full 3-D model for natural backgrounds. The temperatures computed with this model are designed to be input to the radiometric models. Two models have been developed to compute the infrared radiances of natural background scenes, with both spectral and spatial capability. The first model computes radiances from terrain or water, while the second is used for modeling of discrete 3-D objects, such as trees, buildings, and vehicles. Both radiometric models includes thermal emission and reflections of the sun and sky. Atmospheric transmission and radiance are included. The terrain and objects may have spatially-varying temperatures and surface coatings. Emittances and reflectances are spectral and directional/bi- directional. Radiances computed with these models are translated to a Computer Image Generator (CIG) run by the U.S. Army Engineering Topographic Laboratory (ETL) for image rendering.