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Processing images from an infrared imaging seeker for automatic target detection is an extremely complex issue. Many algorithms exist for image feature enhancement, adaptive thresholding, and track file processing. The authors present an overview of imaging signal processing algorithms, including image processing, image segmentation, and track processing with the intent of highlighting the interrelationship between algorithms and the necessity of evaluating seeker algorithms as a whole. The paper also discusses performance metrics for seeker-intercept geometries and the evaluation of metrics in a closed-loop aircraft-intercept simulation.

A numerical model based upon renormalized effective medium theory will be described. The model successfully predicts the frequency dispersive permittivity of finite thickness dielectric/ conducting microsphere composites, electrically lossy syntactic foams, where the conducting particulates have volumetric fraction of 0 to 50%. The composites display unique frequency dispersions which are associated with the composite dimensionality and fractal-like sphere surface morphology. Theory and measurement show the composites have critical volume fractions which can be 20% above theoretical values for conducting spheres, i.e 27-–31% and the frequency dispersion of the composite permittivity can be varied by controlling the nanoscale surface morphology and composite thickness. Supporting permittivity measurements in the frequency range of 1–100 GHz will be presented.