Detection and tracking of single-pixel targets based on trajectory continuity

A target detection and tracking algorithm has been developed to identify single-pixel targets with unknown motion from a time sequence of highly noisy images. The algorithm is based on a target trajectory continuity theory, utilizing temporal continuity and smoothness of target trajectories in both intensity and spatial coordinates in an image plane to detect and simultaneously track multiple targets. With a unique application of the trajectory continuity theory, the algorithm presents an effective engineering solution to the small target track initiation problem in under-speficied environments where an optimum solution is not possible, and at the same time unties the constraint of straight line trajectory that most optimum algorithms require for similar tasks. The algorithm design utilizes a parallel-distributed computing architecture, which aims for real-time target detection and tracking applications.