Acquiring accurate location information of vehicles is of great importance. Global Positioning System (GPS) has been widely deployed and used to be the most convenient solution to outdoor localization. As more and more infrastructure such as elevated roads, tunnels and tall buildings is built, however, the ever-increasing complexity of urban environments makes vehicle localization especially in those urban canyons a new challenging problem. In this paper, we propose a novel scheme, called UPS, to tackle urban vehicle localization problem. Inspired by the observation from empirical study that the Received Signal Strength Indication (RSSI) values of cellular signals (e.g., GSM) perceived over a distance have ideal temporal-spatial characteristics for fingerprinting, UPS refines the location accuracy of a moving vehicle by matching its cellular-aware trajectory, which is an association between consecutive geographical positions and the corresponding wide-band GSM RSSI values, with a pre-constructed map. Moreover, UPS leverages large mobility of vehicles to construct large-scale maps. We implement a prototype system to validate the feasibility of the UPS design. We conduct extensive real-world experiments and results show that UPS can work stably in various urban settings and achieve an accuracy of 4.2 meters on average and 5.3 meters with a 90% precision.

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