MEMBRANE IMMUNOASSAY FOR CHLAMYDIA IDENTIFICATION

Not Available In this proposal we consider the incorporation of advanced image processing techniques into laser tracking algorithms to improve performance in systems such as the AirBorne Laser (ABL) tactical missile defense system. Based on Bayesian and maximum likelihood statistical ideas, and using computationally efficient wavelet filtering methods, our methods sharpen focal plane images allowing for more accurate tracking. Scintillation, the turbulence-induced fluctuation of image intensities, is widely regarded as a major problem for tracking algorithms. The image reconstruction methods we propose herein provide the potential to mitigate significantly the effects of scintillation, thus enhancing track performance. We also propose innovative filtering concepts for tracking algorithms. Collaborating with scientists and engineers at AFRL and at SVS R&D Systems, we will use wave propagation simulations data and data collected in tests at Lincoln Laboratory's Firepond facility to score the performance of these algorithms. Continuing our partnership with SVS, the leader in systems engineering for optical pointing and tracking systems, will allow us to leverage the results obtained in this effort into hardware systems in a most efficient and cost-effective manner.