Bayesian approach to sensor fusion in a multisensor land mine detection system

David Erickson; Ray Kacelenga; David Palmer

doi:10.1117/12.458390

6 March 2002 Bayesian approach to sensor fusion in a multisensor land mine detection system

David Erickson, Ray Kacelenga, David Palmer

Proceedings Volume 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI; (2002) https://doi.org/10.1117/12.458390
Event: AeroSense 2002, 2002, Orlando, FL, United States

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.

Citation Download Citation

David Erickson, Ray Kacelenga, and David Palmer "Bayesian approach to sensor fusion in a multisensor land mine detection system", Proc. SPIE 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI, (6 March 2002); https://doi.org/10.1117/12.458390

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