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Technical Services: Fusion Sciences

Our data fusion work responds to the continually increasing demand for utilizing information from dissimilar sources in efforts to improve the performance beyond using any single data source.

We perform advanced R&D associated with multi-source, multi-sensor, and multi-intelligence data fusion. Emphasis is placed on advanced algorithm development, ontology development, design, and implementation of programs related to optimization, estimation, pattern recognition, and data mining.  

Examples include:

Results in the notion of simultaneous operating processes which effect motivation and consequently decision-making and behavior

Infers what motivations underlie the decisions that an individual or group makes

Models adaptive decisions pertaining to how entities aggregate

Model applicable structural regression network methodologies to explore inferences of significance

Another focus is on the development of innovative approaches for combining the output of space/time features to outcome statistical models with techniques for probabilistic forecasting of behaviors of interest that considers open source information in addition to conventional intelligence data sources. The techniques leveraged in anticipating events include belief nets, Hidden Markov Models and Agent/Source Characterization in order to predict intent based on observations of statistically derived causal features.