Active Target Tracking through Deep Atmospheric Turbulence

In this proposal we consider the development of statistical image processing and filtering techniques for optical tracking in systems such as the AirBorne Laser (ABL) tactical missile defense system. Based on a combination of stochastic modeling fornon-uniform illumination patterns with nonlinear Bayesian filtering, our methods promise to provide greatly enhanced tracking and pointing. Scintillation, the turbulence-induced fluctuation of image intensities, is widely regarded as a major problem fortracking and adaptive optics. The methods we propose herein provide the potential to mitigate significantly the effects of scintillation, thus enhancing system performance. Our estimation techniques are also relevant to problems of anisoplanatism that areof crucial importance in extended range ABL system design. Also included in this effort are the study of data fusion from wavefront sensors and pupil plane imagery and development of robust control designs for pointing. Collaborating with scientists andengineers at Georgia Tech, Trex Enterprises, and AFRL, we will use wave propagation simulations data and data collected in tests at Lincoln Laboratory's ACL facility to score the performance of these algorithms. Our partnership with Trex Enterprises, aleading developer of optical tracking hardware, will allow us to leverage the results obtained in this effort into hardware systems in a most efficient and cost-effective manner.