Measures of effectiveness for high-level fusion

Current advances in technology, sensor collection, data storage, and data distribution have afforded more complex, distributed, and operational information fusion systems (IFSs). IFSs notionally consist of low-level (data collection, registration, and association in time and space) and high-level fusion (user coordination, situational awareness, and mission control). Low-level IFSs typically rely on standard metrics for evaluation such as timeliness, accuracy, and confidence. Given the broader use of IFSs, it is also important to look at high-level fusion processes and determine a set of metrics to test IFSs, such as workload, throughput, and cost. Three types of measures (measures of performance MOP, measures of effectiveness MOE, and measures of merit MOM) are summarized. In this paper, we seek to describe MOEs for High-Level Fusion (HLF) based on developments in Quality of Service (QOS) and Quality of Information (QOI) that support the user and the machine, respectively. We define a HLF MOE based on (1) information quality, (2) robustness, and (3) information gain. We demonstrate the HLF MOE based for a maritime domain situation awareness example.