Abstract

Emerging applications require the location information of clients to enable human-environment interactions or personalized services. With an increasing number of antennas equipped in to- day’s wireless devices, recent research has shown the possibility of sub-meter level localization based only on the angle of arrival (AoA) of WiFi signals. While most existing work provides promising median accuracy, tail performance is usually far worse. We observe from measurements that the root cause is unequal AoA estimation reliability. In some critical areas, a small variation in the channel state information of signals could introduce an extremely large AoA estimation error. With this observation, we propose UAT (Unequal Angle Tracking), a confidence-aware AoA-based localization system. We show that unequal reliability of AoA measures can be mathematically quantified, allowing a system to weigh the estimates of different APs according to their confidence. Our testbed evaluation shows that UATs confidence-aware design provides re- liable decimeter level localization for around 90% of locations.

Bio

Kate Ching-Ju Lin a professor in Department of Computer Science at National Chiao Tung University, HsinChu, Taiwan. Her current research interests include wireless communication and sensing systems, software-defined networking, visible light communications, and internet of things. Dr. Lin has served as PC members in many international conferences, including ACM MOBICOM, USENIX NSDI, IEEE INFOCOM, IEEE ICNP, etc. She is a recipient of the Intel Distinguished Collaborative Research Award. Dr. Lin is an ACM member and IEEE senior member.

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