Track Correlation / Sensor Netting

The tracking and data communication architecture for the current BMDS can be characterized as a “centralized” architecture in that sensor data are sent to a central node for correlation and fusion. Future plans are to evolve this architecture into a “distributed” one where correlation and fusion can occur at multiple nodes throughout the network. The distributed approach is needed to improve scalability and computational load sharing, and it eliminates single point of failure issues. However, to evolve the architecture to a distributed one requires a new distributed correlation-fusion capability. Thus, the goal of this program is to develop a distributed network-centric class of multiple frame data association (or correlation) methods that match the quality of the current centralized multiple hypothesis correlation (MHC) algorithm. Specifically, the new class of methods seeks to achieve a consistent operational picture across the network of platforms, to manage the communications network loading, and to process both IR and radar track reports. Moreover, the proposed distributed architectures will support measurement, tracklet, or track processing. Included in this development are bias estimation, ambiguity assessment of the association process, formation of clusters or complexes, and a cluster track to represent these clusters.