  This paper presents a robust and accurate positioning system that adapts its
behavior to the surrounding environment, mimicking the capability of the visual
brain to filtering out clutter and focusing attention on activity and relevant
information. Especially in indoor environments, which are characterized by
harsh multipath propagation, robust positioning is still hard to achieve under
the constraint of reasonable infrastructural needs. In such environments it is
essential to separate relevant from irrelevant information and attain an
appropriate uncertainty model for measurements that are used for positioning.
