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Proceedings Paper

Algorithms for distributed chemical sensor fusion
Author(s): Scott Lundberg; Randy Paffenroth; Jason Yosinski
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Paper Abstract

The fusion of Chemical, Biological, Radiological, and Nuclear (CBRN) sensor readings from both point and stand-off sensors requires a common space in which to perform estimation. In this paper we suggest a common representational space that allows us to properly assimilate measurements from a variety of different sources while still maintaining the ability to correctly model the structure of CBRN clouds. We design this space with sparse measurement data in mind in such a way that we can estimate not only the location of the cloud but also our uncertainty in that estimate. We contend that a treatment of the uncertainty of an estimate is essential in order to derive actionable information from any sensor system; especially for systems designed to operate with minimal sensor data. A companion paper1 further extends and evaluates the uncertainty management introduced here for assimilating sensor measurements into a common representational space.

Paper Details

Date Published: 15 April 2010
PDF: 12 pages
Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 769806 (15 April 2010); doi: 10.1117/12.849588
Show Author Affiliations
Scott Lundberg, Numerica Corp. (United States)
Randy Paffenroth, Numerica Corp. (United States)
Jason Yosinski, Numerica Corp. (United States)


Published in SPIE Proceedings Vol. 7698:
Signal and Data Processing of Small Targets 2010
Oliver E. Drummond, Editor(s)

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