RF-IR Target Characterization for Feature-Aided Track Correlation

To maintain a complete, timely and coherent situational awareness picture, missile defense command and control functionality typically requires information to be integrated from a variety of different semi-autonomous sensors tracking the battle from different viewing geometries. These sensors, whether EO/IR or RF, typically each develop their own internal tracks upon objects within the scene, which later must be merged together with tracks from other sensors to form a single system track picture that best represents the consensus estimate as to the total number of objects and their trajectories. This track correlation process is complicated both by the fact that the sensors may suffer from uncorrected pointing biases, and also that not all of the sensors will necessarily acquire tracks on all of the objects. Physical Sciences Inc. proposes to improve the performance of the system track correlation process by incorporating time series signature data from the sensors in order to augment the existing distance-based track association metrics that are already currently in use by the system.