Simultaneous Localization and Calibration in a Wireless Network of Uncooperative Nodes

Abstract

Wi-Fi's fine-time measurement (FTM) protocol supports indoor localization with 1-2 m accuracy by allowing two devices to cooperatively measure their signal round-trip-time (RTT). But as of 2023, few commercially-deployed Wi-Fi access points (APs) actually support the protocol.

Using a one-sided RTT measurement technique that does not require cooperation from the AP, a mobile device can obtain distance measurements with most APs in operation today. A major obstacle to using one-sided RTT for localization is that measurements have an unknown bias or offset quantity that is about two orders of magnitude larger than the RTT being measured.

This thesis proposes an algorithmic solution enabling a mobile device to determine its position using only one-sided RTT measurements from uncooperative APs, without prior manual calibration for RTT offsets. Based on the Newton-Gauss method for non-linear least squares problems, it performs both calibration and localization by iteratively updating estimates of position and RTT offset. Experimental results show the solution can achieve about 5 meter, two-dimensional accuracy within the area bounded by APs. Additional characterizations of one-sided RTT range measurements, and the effects of different geometry and frequency bands are also presented.