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Proceedings Paper

Fusion metrics for dynamic situation analysis
Author(s): Erik P. Blasch; Mike Pribilski; Bryan Daughtery; Brian Roscoe; Josh Gunsett
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Paper Abstract

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.

Paper Details

Date Published: 9 August 2004
PDF: 11 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.542902
Show Author Affiliations
Erik P. Blasch, Air Force Research Lab. (United States)
Mike Pribilski, Jacobs Sverdrup (United States)
Bryan Daughtery, Jacobs Sverdrup (United States)
Brian Roscoe, Jacobs Sverdrup (United States)
Josh Gunsett, Jacobs Sverdrup (United States)


Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

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