Advanced Algorithms for Point Target Detection

New developments in neuromorphic concepts permit massively parallel signal processing co-located with the cryogenic focal plane detector array. The Wave Process is a low-contrast moving point target detection algorithm that reduces the data rate todownstream sensor processing, while providing data with a high density of target information. It is efficiently implemented in compact analog VLSI circuits, resulting in small, low-power, low-cost sensors with improved mission performance.In Phase I we showed that the Wave Process can better detect low contrast targets when augmented with Sampled-Time Elementary Motion Detection for isolated noise removal, a positive-feedback gain feature that boosts the target signal, and a shape-findingfunction for pulling very dim targets out of the noise.In Phase II, Tanner Research will integrate these extensions, the Adaptive Speed feature (developed on a parallel AFRL/MN contract), and additional concepts (e.g., Optical Flow), into an Advanced Wave Process. We will demonstrate the improved missionperformance with high-fidelity simulations and validated imagery data sets representing scenarios relevant to AFRL. We will optionally apply these developments to the specific requirements of identified DoD missions and systems (e.g., UAV, cruise missiledetection, Air Superiority Missile, etc.).