Approaches to information fusion with spatiotemporal aspects for standoff and other biodefense information sources
2010
This paper discusses some of the techniques developed at MIT Lincoln Laboratory for information fusion of lidar-based
biological standoff sensors, meteorology, point sensors, and potentially other information sources, for biodefense
applications. The developed Spatiotemporal Coherence (STC) fusion approach includes phenomenology aspects and
approximate uncertainty measures for information corroboration quantification. A supervised machine-learning
approach was also developed. Computational experiments involved ground-truth data generated from measurements and
by simulation techniques that were developed. The fusion results include performance measures that focus explicitly on
the fusion algorithms' effectiveness. Both fusion approaches enable significant false-alarm reduction. Their respective
advantages and tradeoffs are examined.
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