Continuous belief functions to qualify sensors performances

Authors:
Pierre-Emmanuel Doré;Christophe Osswald;Arnaud Martin;Anne-Laure Jousselme;Patrick Maupin
Affiliations:
E³I², ENSTA Bretagne, Brest Cedex 9, France;E³I², ENSTA Bretagne, Brest Cedex 9, France;IRISA, Université de Rennes 1, Lannion, France;R & D Defence Canada-Valcartier, Decision Support Systems for Command and Control, Quebec, QC, Canada;R & D Defence Canada-Valcartier, Decision Support Systems for Command and Control, Quebec, QC, Canada
Venue:
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Year:
2011

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Abstract

In this paper, we deal with the problem of sensor performance estimation. As we assume that the sensor is described with only few data, we decide to use the theory of belief functions to represent the inherent uncertainty of our information. Hence, we introduce the belief functions framework, especially in the continuous approach. We describe the model of sensor adopted in our study. Knowing the experimental setting, we suggest an approach to model the sources of information describing our sensor. Finally, we combine these sources in order to estimate sensor performances.