Data Fusion for Missile Defense

In a Ballistic Missile Defense scenario, sensors will be faced with trying to identify and track targets in a scenario composed of decoys, Electronic Counter Measures, and associated missile fragments.The objective of this is to develop algorithms, concepts and techniques that utilize ground, high-altitude, or satellite sensor data together with onboard missile/kill-vehicle sensors to provide an enhanced target discrimination capability.Sensis proposes Multi-Sensor Track (MST) algorithm modified to a Multi-Hypothesis Multi-Sensor Data Fusion System (MH-MS-DF) to fuse data derived from ground, high-altitude or satellite sensor data. The association algorithm of the MH-MS-DF will have thecapability to adjust for time mis-alignment of data sources, missed detections, false alarms, incorrect sensor ID information, dynamic data association gates, and sensor registration limits.During Phase I, Sensis shall develop concepts and techniques for a Multi-Hypothesis Multi-Sensor Data Fusion System derived by extending the capabilities of a Sensis developed Multi-Sensor Track algorithm.During Phase II, Sensis will develop software algorithms to implement and demonstrate the MH-MS-DF algorithms derived in Phase I.During Phase III, Sensis will promote dual use application of the MH-MS-DF to civilian problems such as Drug Interdiction, Air Traffic Control, Medical Applications, and Homeland Defense Initiatives. Defense related Applications include:Automatic SurveillanceMinimization of Friendly Fire CasualtiesTarget Tracking, Location and IdentificationCommercial ApplicationsTransportation Systems (Location of trucks, railway cars, ships, and aircraft)Drug Enforcement Agency (aerial drug interdiction)DOD Homeland Security (detect and track aircraft where the transponder replies are not being received)Intelligent Vehicle Highway Systems (IVHS) (traffic control)