Fusion metrics for dynamic situation analysis
Erik Blasch, Mike Pribilski, Bryan Daughtery, Brian J. Roscoe, Josh Gunsett · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
To design information fusion systems, it is important to develop metrics as part of a test and evaluation strategy. In many cases, fusion systems are designed to (1) meet a specific set of user information needs (IN), (2) continuously validate information pedigree and updates, and (3) maintain this performance under changing conditions. A fusion system’s performance is evaluated in many ways. However, developing a consistent set of metrics is important for standardization. For example, many track and identification metrics have been proposed for fusion analysis. To evaluate a complete fusion system performance, level 4 sensor management and level 5 user refinement metrics need to be developed simultaneously to determine whether or not the fusion system is meeting information needs. To describe fusion performance, the fusion community needs to agree on a minimum set of metrics for user assessment and algorithm comparison. We suggest that such a minimum set should include feasible metrics of accuracy, confidence, throughput, timeliness, and cost. These metrics can be computed as confidence (probability), accuracy (error), timeliness (delay), throughput (amount) and cost (dollars). In this paper, we explore an aggregate set of metrics for fusion evaluation and demonstrate with information need metrics for dynamic situation analysis.