Sensor Data Fusion

Today’s fusion and tracking systems rely on sensor feeds and a-priori information to process and relate collected information. Little information is extracted from imagery data such as FLIR, SAR and EO; not enough emphasis is placed on sensor pedigree and confidence (uncertainty); and therefore networked Multi-INT sensors are not fully exploited. This proposal describes a process for combining emerging Multi-INT sensor fusion algorithms within a generic fusion exploitation framework to enhance the user’s battlespace awareness thru automated sensor data fusion and visualization. Potomac Fusion’s ‘Fusion Exploitation Framework’ combines sensor information (collected using a community agreed upon standard) with a workflow that processes modular, integrated fusion algorithms that exploit SIGINT and imagery-based information to produce a more accurate picture of the threat. Using sensors that collect on various aspects of the problem such as: o Different parts of the RF spectrum o Using SAR, EO, IR for target recognition o Composite/Feature extraction from Hyper-spectral, Radar, EO, and various IR capabilities we are able to more completely and confidently identify and categorize the observed information.