Positioning has been a driving factor in the development of ubiquitous computing applications throughout the past two decades. Numerous devices and techniques have been developed - few of them are actually used commercially. Within the NOMAD project, multiple methods are being combined to recalibrate each other by means of data fusion. A novel architecture processes the data from pervasive devices penetrating everyday objects to the cheapest level. The synergetic heterogeneity of completely different recognition principles allows to tailor the perceived positioning probability to the specific requirements of the target application.