“AnguLoc: Concurrent angle of arrival estimation for indoor localization with UWB radios” by Milad Heydariaan, Hossein Dabirian, and Omprakash Gnawali. In Proceedings of the Sixteenth International Conference on Distributed Computing in Sensor Systems (DCOSS 2020), June 2020.
The angle of arrival (AoA) estimation is one of the commonly used techniques for indoor localization. Ultrawideband (UWB) radios facilitate AoA estimation through the measurement of the phase difference of arrival (PDoA) at multiple receiver antennas. Concurrent transmissions in UWB radios aim to increase the efficiency of localization systems by exploiting wireless interference. This paper first investigates the feasibility of AoA estimation with UWB radios in a concurrent scheme. State-of-the-art UWB indoor localization solutions use time difference of arrival (TDoA) in a concurrent scheme. These solutions rely on accurate timestamping of the concurrently received packets. However, due to the scheduling uncertainty of the UWB transmitter platform used in this area, an unavoidable timing jitter of 8 ns causes up to 2.4 m of the localization error. Therefore, the accuracy of solutions based on concurrent TDoA relies on additional timestamp correction, which adds to the complexity of the system. Our results show that concurrent AoA estimation remains unaffected by the transmitter scheduling uncertainties. AoA-based localization techniques face two main challenges: (1) front-back ambiguity of AoA for antenna array of size two; and (2) AoA measurement device's unknown tilting. This paper then presents AnguLoc, an efficient and scalable indoor localization system that makes use of concurrent AoA estimation to reduce the number of required packet exchanges. AnguLoc uses an Angle Difference of Arrival (ADoA) technique, also generalizable to sequential AoA, to overcome the front-back angle measurement ambiguity problem, and to work with unknown tag tilting. We evaluate AnguLoc in an office environment on a recently introduced platform, Decawave PDoA node (DWM1002). Our results show that AnguLoc is 4 times faster than sequential AoA and improves the localization accuracy by up to 44.33% compared to state-of-the-art concurrency-based indoor localization solutions without relying on additional timestamp correction.
BibTeX entry:
@inproceedings{anguloc-dcoss20,
author = {Milad Heydariaan and Hossein Dabirian and Omprakash Gnawali},
title = {AnguLoc: Concurrent angle of arrival estimation for indoor
localization with UWB radios},
booktitle = {Proceedings of the Sixteenth International Conference on
Distributed Computing in Sensor Systems (DCOSS 2020)},
month = jun,
year = {2020}
}