  In this paper, we take a new approach for time of arrival geo-localization.
We show that the main sources of error in metropolitan areas are due to
environmental imperfections that bias our solutions, and that we can rely on a
probabilistic model to learn and compensate for them. The resulting
localization error is validated using measurements from a live LTE cellular
network to be less than 10 meters, representing an order-of-magnitude
improvement.
