Surface reflectance variations in realistic targets

Signature prediction models have become an increasingly important tool for the ground combat vehicle designer in recent years. System designers have been successful in prototyping entire vehicles in each spectral band. With this success, focused efforts to improve the accuracy of these signature models have produced robust, validated performance for many operational conditions. One of the most recent improvement in prediction models for ground vehicle systems has been improvements in surface reflectance. Surface reflectance is central to the predicted performance of these models and range from simple to very complex. Simple surface reflectance models treats the surface as totally lambertiant has an advantage of being fast to calculate but does not take into account the specular nature which all surfaces posses. The bi-directional reflectance distribution function (BRDF) is a more complex representation which allows for a more accurate representation of surface reflectance phenomena. The input to the BRDF usually comes from a laboratory sample measured in a laboratory setting. These laboratory samples are made to be perfect so that comparisons can be made between variations in formulas for the coatings. The limitation of these inputs is that surfaces that are exposed to environments effects and normal daily use are the more representative of data we are interested in. Other effects such as the conditions under which the surface coatings are applied can cause reflectance variability as well. This paper explores the variability on real targets and compares them to laboratory samples. The implication of these variations to signature models will be explored.