Sensor Data Fusion

The task of identifying and successfully destroying a missile threat requires a vast network of RADARs, sensors, software, and other resources working together flawlessly. Information from these systems must be fused to provide with their operators an accurate and complete picture of the battlespace. With up-to-date, fused information on threats and targets, operators can make quick, informed decisions. Creating this accurate picture of the battlespace requires many different RADARs dispersed around the globe. By combining data from different views and different features, a much more detail picture can be formed. However, translation of all of this data into concise, useful, and timely information remains extremely difficult. Recognizing this need, the DoD is seeking methods to improve their ability to fuse sensor data and ultimately deliver an accurate comprehensive picture of the battlespace. The proposed EDAptive® RIFRAF solution meets these needs by delivering a flexible framework for sensor fusion and knowledge representation. The resulting capabilities will result in new methods for developing sensor fusion algorithms and allow the MDA to continue to expand and improve its global sensor network with confidence.