The belief function theory within the framework of localizing an object

This paper attempts to show and apply the principle of information fusion of the belief function theory to the localization context. In fact, the main objective is to use imprecise and uncertain information stemming from two categories of sensors that are used to estimate the position of an object. What is more, we try to benefit from the advantages presenting the belief function theory, especially when they are compared to the probability approach, so as to consider the disjunctions and model the notions of uncertainty and imprecision.