Publication | Open Access
ToneTrack
325
Citations
62
References
2015
Year
Unknown Venue
Wireless CommunicationsRf LocalizationEngineeringWireless LanMobile DevicesLocation AwarenessMobile ComputingInternet Of ThingsFrequency-agile Wireless NetworksIndoor Positioning SystemLocalizationSignal ProcessingIndoor LocalizationRadio Local Area Network
Indoor localization has achieved fine‑grained accuracy with line‑of‑sight, but time‑of‑arrival methods are limited by narrow bandwidth; frequency‑agile networks can exploit varying bandwidths to improve resolution. ToneTrack aims to deliver sub‑meter indoor positioning using minimal hardware by exploiting frequency‑agile networks to boost effective bandwidth. ToneTrack combines time‑of‑arrival data from multiple channels using a novel signal‑combination algorithm and a triangle‑inequality scheme, implemented on WARP radios with six APs. Experiments show ToneTrack achieves median 90 cm accuracy even with one to two walls or complete blockage, outperforming single‑band methods.
Indoor localization of mobile devices and tags has received much attention recently, with encouraging fine-grained localization results available with enough line-of-sight coverage and hardware infrastructure. Some of the most promising techniques analyze the time-of-arrival of incoming signals, but the limited bandwidth available to most wireless transmissions fundamentally constrains their resolution. Frequency-agile wireless networks utilize bandwidths of varying sizes and locations in a wireless band to efficiently share the wireless medium between users. ToneTrack is an indoor location system that achieves sub-meter accuracy with minimal hardware and antennas, by leveraging frequency-agile wireless networks to increase the effective bandwidth. Our novel signal combination algorithm combines time-of-arrival data from different transmissions as a mobile device hops across different channels, approaching time resolutions previously not possible with a single narrowband channel. ToneTrack's novel channel combination and spectrum identification algorithms together with the triangle inequality scheme yield superior results even in non-line-of-sight scenarios with one to two walls separating client and APs and also in the case where the direct path from mobile client to an AP is completely blocked. We implement ToneTrack on the WARP hardware radio platform and use six of them served as APs to localize Wi-Fi clients in an indoor testbed over one floor of an office building. Experimental results show that ToneTrack can achieve a median 90 cm accuracy when 20 MHz bandwidth APs overhear three packets from adjacent channels.
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