Robust Adaptive Spatial-Temporal Algorithms for Clutter Rejection and Scene Stabilization

The problem of efficient clutter suppression is a challenge for space-based infrared sensors that have to provide early detection/tracking of missiles launches in cloud solar backgrounds. In such systems, reliable target tracking is impossible without clutter rejection down to/below the level of sensor noise. In Phase I we developed novel parametric and nonparametric spatial-temporal techniques for clutter rejection and image stabilization as well as clutter simulation tools for simulation of backgrounds for various conditions. As we have demonstrated in Phase I, our spatial-temporal methods are particularly efficient for target detection/tracking in difficult scenarios when spatial-only filters completely fail. The Phase II proposal is geared towards improving performance of the clutter filtering and jitter compensation algorithms; development of a bank of clutter suppression/stabilization filters with outlier compensation and an adaptive reconfigurable architecture; target detection/tracking algorithms; and testing/demonstrating the capabilities of the developed technology in realistic environments. The developed software imbedded into a GUI interface will constitute a powerful tool for the optimization of operational target detection/tracking systems in conditions of interest. These software tools will be also capable of predicting the performance and reducing to a minimum the time needed to search for an optimal system configuration in MDA programs/systems.