This paper addresses the use of implication rules (with uncertainty) within the Transferable Belief Model (TBM)
where the rules convey knowledge about relationships between two frames of discernment. Technical challenges
include: a) computational scalability of belief propagation, b) logical consistency of the rules, and c) uncertainty
of the rules. This paper presents a simplification of the formalism developed by Ristic and Smets for incorporating
uncertain implication rules into the TBM. By imposing two constraints on the form of implication rules, and
restricting results to singletons of the frame of discernment, we derive a belief function that can be evaluated in
This paper addresses the problem of multi-source object classication in a context where objects of interest are
part of a known taxonomy and the classication sources report at varying levels of specicity. This problem
must consider several technical challenges: a) support fusion of heterogeneous classication inputs, b) provide a
computationally scalable approach that accommodates taxonomy's with thousands of leaf nodes, and c) provide
outputs that support tactical decision aides and are suitable inputs for subsequent fusion processes. This paper
presents an approach that employs the Transferable Belief Model, Pignistic Transforms, and Bayesian Fusion to
address these challenges.
Evaluating the effectiveness of fusion systems in a multi-sensor, multi-platform environment has historically been a
tedious and time-consuming process. Typically it has been necessary to perform data collection and analysis in different
code baselines, which requires error-prone data format conversions and manual spatial-temporal data registration. The
Metrics Assessment System (MAS) has been developed to provide automated, real-time metrics calculation and display.
MAS presents metrics in tables, graphs, and overlays within a tactical display. Comparative assessments are based on
truth tracks, including position, velocity, and classification information. The system provides tabular history drill-down
for each metric and each track. MAS, which is currently being evaluated on anti-submarine warfare scenarios, can be a
valuable tool both in objective evaluation performance of tracking and fusion algorithms and in identifying asset and
target interactions that cause the fused tracks to generate from the true ones.