The proposed effort will research innovative algorithms to exploit novel target signatures for insertion into ground-based processing software and real-time spacecraft data-processing firmware. We exploit novel dim phenomena (targets, events, and environmental phenomena of military relevance) based on a novel mathematical technique, dynamic logic (DL). DL overcame computational complexity plaguing algorithms for signal processing, estimation, and tracking in clutter since the 1960s. DL resulted in orders of magnitude improvement (100 times and better) of signal-to-noise and signal-to-clutter performance of track-before-detect and detecting phenomena of military relevance. DL algorithms use statistical and model-based clutter and noise models with parameters estimated from data concurrently with clutter and target detection and tracking. They are unique in achieving Cramer-Rao Bounds for best possible estimation in noise and clutter. DL algorithms for GMTI have been transitioned to intelligence and received endorsements from analysts, General Officers, and two DepSecDef. Here we propose to bring this breakthrough research to electro-optical, SWIR surveillance for dim phenomena, noise and clutter mitigation, TPE, fast and slow moving objects, transients, and other applications of interest. Based on the past transition successes the new algorithms will be successfully inserted into existing baseline OPIR software and successfully perform in real-time on flight-like hardware.
Benefit: Significant improvement of data-processing methods and algorithms to exploit novel target signatures will be developed for insertion into ground-based processing software and real-time spacecraft data-processing firmware. These methods and algorithms will exploit novel dim phenomena (targets, events, and environmental phenomena of military relevance). They will mitigate artifacts, e.g., noise, internal reflections, etc., they will use innovative clutter suppression and mitigation techniques for SWIR see-to-ground bands (e.g., static sources, slow- or fast-moving objects), as well as track-before-detect approaches. The developed algorithms will be inserted into existing baseline overhead persistent infrared (OPIR) software, at facilities such as the Aerospace Fusion Center, and the utility of the algorithms will be tested on flight-like hardware. The proposed effort will result in improved exploitation of SWIR image data acquired by space-based sensors viewing earth scenes. Potential commercialization applications will include DoD programs of record for space-based surveillance as well as new approaches for OPIR replenishment and modernization. In addition to expanding military applications, business commercial applications will be explored. These will include IR sensing and signal processing relevant to space-based weather information services, new environmental monitoring capabilities, and geophysical exploration.
Keywords: Infrared data, data
