Continuous belief functions to qualify sensors performances

Pierre-Emmanuel Doré (1, 2) , Christophe Osswald (1, 2) , Arnaud Martin (3)

1 E3I2 - Extraction et Exploitation de l'Information en Environnements Incertains
2 STIC - Département STIC [Brest]
3 CORDIAL - Human-machine spoken dialogue

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.

Mots clés: Sensor performances; Continuous belief function; Parametric model; Inference; Fusion

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Pierre-Emmanuel Doré, Christophe Osswald, Arnaud Martin. Continuous belief functions to qualify sensors performances. ESQARU 2011, Jun 2011, Belfast, Ireland. ⟨hal-00636049⟩