Report-to-Track Data Fusion

Though data fusion technology has made significant strides in the last few years, combat systems still need a more reliable way to combine and resolve target data from multiple onboard and off-board sensors. Users of data fusion need a way to select among competing data fusion technologies. Additionally, a data fusion algorithm that was developed for a specific problem space may have broader applicability that is difficult to uncover using traditional "solve the problem at hand" acquisition processes. There is no convenient way for customers to evaluate data fusion algorithms from a variety of suppliers or to evaluate data fusion algorithms designed for one environment against a different environment. There is no way to objectively determine "best of breed" across multiple domains. SimVentions proposes the establishment of a Data Fusion Algorithm Simulation, Stimulation, and Evaluation Tool (DF-ASSET) that provides a realistic, repeatable, verified, and validated source of sensor reports to data fusion algorithm(s), and then computes metrics to measure the correctness and performance of the algorithm(s) against ground truth and each other. DF-ASSET is a modular, open, component-based test bed that generates representative sensor data from predefined scenarios, feeding data to a component containing "data fusion algorithm(s)."