RT Journal Article
T1 Probabilistic Time of Arrival Localization
A1 Pérez Cruz, Fernando
A1 Martínez Olmos, Pablo
A1 Minyi Zhang, Michael
A1 Huang, Howard
AB In this letter, 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.
PB IEEE
SN 1070-9908
YR 2019
FD 2019-11
LK https://hdl.handle.net/10016/32740
UL https://hdl.handle.net/10016/32740
LA eng
DS e-Archivo
RD 27 jul. 2024