When FTM Discovered MUSIC: Accurate WiFi-based Ranging in the Presence of Multipath

Abstract

The recent standardization by IEEE of Fine Timing Measurement (FTM), a time-of-flight based approach for ranging has the potential to be a turning point in bridging the gap between the rich literature on indoor localization and the so-far tepid market adoption. However, experiments with the first WiFi cards supporting FTM show that while it offers meter-level ranging in clear line-of-sight settings (LOS), its accuracy can collapse in non-line-of-sight (NLOS) scenarios. We present FUSIC, the first approach that extends FTM's LOS accuracy to NLOS settings, without requiring any changes to the standard. To accomplish this, FUSIC leverages the results from FTM and MUSIC-both erroneous in NLOS-into solving the double challenge of 1) detecting when FTM returns an inaccurate value and 2) correcting the errors as necessary. Experiments in 4 different physical locations reveal that a) FUSIC extends FTM's LOS ranging accuracy to NLOS settings-hence, achieving its stated goal; b) it significantly improves FTM's capability to offer room-level indoor positioning.

Accurate ubiquitous localization with off-the-shelf IEEE 802.11ac devices

“…FUSIC [26] is based on ToF measurements to determine the device position. It relies on FTM ranging and uses the 1-dimensional MUSIC algorithm to reduce multipath effects.…”

“…Estimating the absolute ToF and thus the distance between client and AP requires timestamped packet exchanges, as standardized in the 802.11 Fine Timing Measurement (FTM) protocol [23,24]. However, FTM is inaccurate in multipathrich environments [26]. UbiLocate uses a custom protocol similar to FTM that has lower overhead and is more robust by decomposing the multipath channel to accurately determine the ToF of the first path.…”

“…(i) UbiLocate is the first location system implemented on off-the-shelf devices that works with 80 MHz WiFi channels and does not require a nondisclosure agreement (the existing 80 MHz location systems [5,40] use Quantenna devices that require such a non-disclosure agreement). (ii) It is also the first IEEE 802.11ac-based location system that can simultaneously derive both angle and absolute distance to a target device, whereas prior work uses two separate co-located devices for this purpose [26,40].…”

Enhanced Wi-Fi RTT Ranging: A Sensor-Aided Learning Approach

“…Certain studies investigated methods to improve the ranging accuracy using both RSS and RTT measurements [33], [37] or multiple RTT measurements obtained from different frequency bands [44]. Moreover, a high-resolution estimation technique was proposed to improve the ranging accuracy when the CSI of FTM packets is available [42]. In the positioning stage, Bayesian filtering techniques have been applied to track the location of mobile devices using a series of ranging results.…”

“…However, the FTM protocol is known to produce biased ranging outputs, which must be calibrated to achieve accurate ranging and positioning performances. Furthermore, some papers indicated that the FTM protocol generates a higher number of ranging errors in non-line-of-sight (NLOS) conditions than that in line-of-sight (LOS) conditions [42], [47]. In this situation, this work studies a machine learning-based approach to obtain precise ranging results.…”