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Accurate and reliable positioning is an important prerequisite for numerous vehicular applications. Localization techniques based on satellite navigation systems are nowadays standard and deployed in most commercial vehicles. When such a standalone positioning is used in challenging environments like dense urban areas, the localization performance often dramatically degrades due to blocked and reflected satellites signals. In this paper, a general and lightweight probabilistic positioning algorithm with integrated multipath detection through 3D environmental building models is presented. It will be shown that the proposed system outperforms-in terms of accuracy and integrity-existing methods without introducing additional hardware sensors. Furthermore, a benefit analysis of the suggested 3D model for tightly and loosely coupled GPS/INS sensor integration schemas is provided. Finally, the algorithm will be evaluated with real-world data collected during an urban measurement campaign.