Advanced Clutter Suppression Techniques for Space Based Infrared Sensors

This proposal addresses the problem of identifying and testing clutter suppression techniques and implementing algorithms for detection of targets imbedded in cluttered terrain backgrounds. Tactical remote sensing systems such as Warfighter must carry out their target detection and identification mission against a wide variety of earth background scenes having an as yet undetermined range of clutter properties. Hence, such sensors must be capable of utilizing the spectral, temporal, and spatial dimensions of the target signature while rejecting or mitigating the background clutter. In order to optimize the sensor performance against widely ranging, sometimes poorly defined engagement scenarios, it is necessary to account for the effects of sensor system optical and electronic performance on implementation of clutter suppression and target signal optimization techniques. The process of implementing and optimizing clutter suppression algorithms for proposed tactical testbeds such as MightySat and Warfighter must also address practical systems considerations such as sensor and signal processing complexity, cost, and on-orbit weight and power utilization required for combined sensor and target detection signal processing system. The proposed research will identify and test one or more innovative clutter suppression algorithms in the context of the Warfighter sensor scenario. Benefits: The anticipated commercial applications of this research are background scene content recognition and discrimination models and algorithms based upon the clutter rejection algorithms which are the subject of this SBIR research.|