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Proceedings Paper

Bayesian approach to sensor fusion in a multisensor land mine detection system
Author(s): David Erickson; Ray Kacelenga; David Palmer
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Paper Abstract

In the present study, the investigation by General Dynamics Canada, formerly Computing Devices Canada, into Bayesian Inference shows improved sensor fusion of multiple scanning sensors in the detection of buried anti-tank (AT) mines. This algorithm uses statistical data taken from trials and constructs conditional probabilities for individual sensors in order to better discern landmines.

Paper Details

Date Published: 6 March 2002
PDF: 11 pages
Proc. SPIE 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI, (6 March 2002); doi: 10.1117/12.458390
Show Author Affiliations
David Erickson, General Dynamics Canada Ltd. (Canada)
Ray Kacelenga, General Dynamics Canada Ltd. (Canada)
David Palmer, General Dynamics Canada Ltd. (Canada)


Published in SPIE Proceedings Vol. 4731:
Sensor Fusion: Architectures, Algorithms, and Applications VI
Belur V. Dasarathy, Editor(s)

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