Image-Based Tracking for Smart Muintions

In this proposal we consider the development of statistical image processing, tracking, and guidance technologies for navigation, guidance, and control in advanced smart munitions. The archetypal example system in which we are interested is the LOCAASsmart munition. The algorithms we propose to develop, however, will be broadly applicable to any number of seeker, interceptor, and semi-autonomous munition systems.Leveraging recent research in optical flow and active contours with proven filtering technologies of direct applicability in tracking for systems such as the Air Borne Laser, we will develop a suite of algorithms to determine feature positions over timewithin scenes observed by imaging-sensor-bearing munitions. The feature positions over time are then to be used for improved track and guidance accuracy. Much more general and flexible than traditional correlation trackers, the optical flow methodologyadapts well to scaling and aspect angle changes. Coupled with efficient temporal models and filters, the optical flow and active contours can maintain the location of multiple targets in a scene with great accuracy. Potential commercial applications will be primarily of a military nature, as the effort proposed herein is heavily focused toward advancing LOCAAS and other munitions systems capabilities. Other optical tracking and imaging systems will benefit, however,from improvements derived from this research. Entertainment technologies related to motion capture and animation offer a variety of potential commercial applications.