Probabilistic Time of Arrival Localization
arXiv:1910.06569 · doi:10.1109/LSP.2019.2944005
Abstract
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.
IEEE Signal Processing Letters, 2019