TY - GEN
T1 - Smartphone positioning with radio measurements from a single wifi access point
AU - Rea, Maurizio
AU - Abrudan, Traian Emanuel
AU - Giustiniano, Domenico
AU - Claussen, Holger
AU - Kolmonen, Veli Matti
N1 - Publisher Copyright:
© 2019 ACM.
PY - 2019/12/3
Y1 - 2019/12/3
N2 - Despite the large literature on localization, there is no solution yet to localize a commercial off-the-shelf smartphone device using radio measurements from a single WiFi AP. We present SPRING, Smartphone Positioning with Radio measurements from a sINGle wifi access point. SPRING exploits Fine Time Measurements (FTM) and Angle of Arrival (AOA) extracted from commercial chipsets exploiting the specifications of the recent 802.11-2016 and the 802.11ac amendment to combine distance and direction from the AP to the client for positioning. Our system has the potential to bring indoor positioning to homes and small businesses which typically have a single access point. We exploit physical layer (PHY) information to detect the number of paths and their directions. We use this information to derive a new method for filtering ranging measurements obtained with the FTM protocol. We achieve sub-meter distance estimation accuracy eliminating the adverse effect of multipath in FTM using calibrated inputs from Channel State Information (CSI). Our evaluation in indoor scenarios in multipath rich environments demonstrates that the combination of AOA estimation and the proposed FTM refinement approach can locate a Google Pixel 3 smartphone with a median positioning error of 0.9-2.15 m through an area comparable to typical flat sizes.
AB - Despite the large literature on localization, there is no solution yet to localize a commercial off-the-shelf smartphone device using radio measurements from a single WiFi AP. We present SPRING, Smartphone Positioning with Radio measurements from a sINGle wifi access point. SPRING exploits Fine Time Measurements (FTM) and Angle of Arrival (AOA) extracted from commercial chipsets exploiting the specifications of the recent 802.11-2016 and the 802.11ac amendment to combine distance and direction from the AP to the client for positioning. Our system has the potential to bring indoor positioning to homes and small businesses which typically have a single access point. We exploit physical layer (PHY) information to detect the number of paths and their directions. We use this information to derive a new method for filtering ranging measurements obtained with the FTM protocol. We achieve sub-meter distance estimation accuracy eliminating the adverse effect of multipath in FTM using calibrated inputs from Channel State Information (CSI). Our evaluation in indoor scenarios in multipath rich environments demonstrates that the combination of AOA estimation and the proposed FTM refinement approach can locate a Google Pixel 3 smartphone with a median positioning error of 0.9-2.15 m through an area comparable to typical flat sizes.
KW - Angle of arrival
KW - Channel state information
KW - Fine time measurements
KW - Localization system
UR - https://www.scopus.com/pages/publications/85077230151
U2 - 10.1145/3359989.3365427
DO - 10.1145/3359989.3365427
M3 - Conference proceeding
AN - SCOPUS:85077230151
T3 - CoNEXT 2019 - Proceedings of the 15th International Conference on Emerging Networking Experiments and Technologies
SP - 200
EP - 206
BT - CoNEXT 2019 - Proceedings of the 15th International Conference on Emerging Networking Experiments and Technologies
PB - Association for Computing Machinery, Inc
T2 - 15th ACM International Conference on Emerging Networking Experiments and Technologies, CoNEXT 2019
Y2 - 9 December 2019 through 12 December 2019
ER -