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Proceedings Paper

Practical considerations in Bayesian fusion of point sensors
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Paper Abstract

Sensor data fusion is and has been a topic of considerable research, but rigorous and quantitative understanding of the benefits of fusing specific types of sensor data remains elusive. Often, sensor fusion is performed on an ad hoc basis with the assumption that overall detection capabilities will improve, only to discover later, after expensive and time consuming laboratory and/or field testing that little advantage was gained. The work presented here will discuss these issues with theoretical and practical considerations in the context of fusing chemical sensors with binary outputs. Results are given for the potential performance gains one could expect with such systems, as well as the practical difficulties involved in implementing an optimal Bayesian fusion strategy with realistic scenarios. Finally, a discussion of the biases that inaccurate statistical estimates introduce into the results and their consequences is presented.

Paper Details

Date Published: 10 May 2012
PDF: 10 pages
Proc. SPIE 8407, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012, 84070X (10 May 2012); doi: 10.1117/12.920817
Show Author Affiliations
Kevin Johnson, Naval Research Lab. (United States)
Christian Minor, Nova Research, Inc. (United States)


Published in SPIE Proceedings Vol. 8407:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012
Jerome J. Braun, Editor(s)

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