Paper
15 April 2010 Algorithms for distributed chemical sensor fusion
Author Affiliations +
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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Scott Lundberg, Randy Paffenroth, and Jason Yosinski "Algorithms for distributed chemical sensor fusion", Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 769806 (15 April 2010); https://doi.org/10.1117/12.849588
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Clouds

Chemical analysis

Diffusion

Data modeling

Infrared sensors

Chemical fiber sensors

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