Dejavu: An Accurate Energy-Efficient Outdoor Localization System

We present Dejavu, a system that uses standard cell-phone sensors to provide accurate and energy-efficient outdoor lo-calization suitable for car navigation. Our analysis shows that different road landmarks have a unique signature on cell-phone sensors; For example, going inside tunnels, mov-ing over bumps, going up a bridge, and even potholes all affect the inertial sensors on the phone in a unique pattern. Dejavu employs a dead-reckoning localization approach and leverages these road landmarks, among other automatically discovered abundant virtual landmarks, to reset the accumu-lated error and achieve accurate localization. To maintain a low energy profile, Dejavu uses only energy-efficient sensors or sensors that are already running for other purposes. We present the design of Dejavu and how it leverages crowd-sourcing to automatically learn virtual landmarks and their locations. Our evaluation results from implementation on different android devices in both city and highway driving show that Dejavu can localize cell phones to within 8.4 m median error in city roads and 16.6 m on highways. More-over, compared to GPS and other state-of-the-art systems, Dejavu can extend the battery lifetime by 347%, achieving even better localization results than GPS in the more chal-lenging in-city driving conditions