Peer-to-Peer Localization for Single-Antenna Devices

TL;DR

P2PLocate is a novel peer-to-peer indoor localization system that uses multipath variations and user movements with single-antenna devices, achieving decimeter-level accuracy without infrastructure or pre-training.

Contribution

It introduces a new localization method leveraging on-body backscatter tags and movement cues, eliminating the need for pre-deployed infrastructure or multiple antennas.

Findings

Median localization accuracy of 0.88 meters in real-world tests

Effective for both static and mobile targets

Operates with commercial off-the-shelf hardware

Abstract

Some important indoor localization applications, such as localizing a lost kid in a shopping mall, call for a new peer-to-peer localization technique that can localize an individual's smartphone or wearables by directly using another's on-body devices in unknown indoor environments. However, current localization solutions either require pre-deployed infrastructures or multiple antennas in both transceivers, impending their wide-scale application. In this paper, we present P2PLocate, a peer-to-peer localization system that enables a single-antenna device co-located with a batteryless backscatter tag to localize another single-antenna device with decimeter-level accuracy. P2PLocate leverages the multipath variations intentionally created by an on-body backscatter tag, coupled with spatial information offered by user movements, to accomplish this objective without relying on any pre-deployed infrastructures or pre-training. P2PLocate incorporates novel algorithms to address two major challenges: (i) interference with strong direct-path signal while extracting multipath variations, and (ii) lack of direction information while using single-antenna transceivers. We implement P2PLocate on commercial off-the-shelf Google Nexus 6p, Intel 5300 WiFi card, and Raspberry Pi B4. Real-world experiments reveal that P2PLocate can localize both static and mobile targets with a median accuracy of 0.88 m.