IDENTIFICATION OF NOVEL IMMUNOSUPPRESSIVE AGENTS

Not Available Multispectral imaging offers significant advantages over conventional imaging by providing diversity data to detect camouflaged or low-contrast targets, reduce complex scene clutter and identify materials. Passive multispectral imaging is susceptible to undesirable and often uncontrollable effects such as changes in illumination angle and intensity, diurnal cycles, and varying material emissivities. Active sensors overcome these limitations and also provide discriminates not readily available in passive sensors, such as degree of polarization and range information. In Phase I, CTI will develop an optical scattermodel that combines physics-based scattering phenomena (diffuse and glint reflections, depolarization, etc.) with empirical data (bidirectional reflectance) to determine an optimal feature vector for materials classification. The model will be incorporated into CTI's existing comprehensive coherent and direct detection laser radar performance modeling suit to determine the optimal multispectral sensor design for enhanced contrast target detection. In Phase II, an active imaging sensor based upon the optimal architecture chosen in Phase I will be designed and fabricated for initial laboratory and field tests. The proposed work leverages CTI's expertise in developing frequency agile lasers, flight-worthy transceivers and signal processors.