An analysis of the properties and the performance of WiFi RTT for indoor positioning in non-line-of-sight environments

Xu Feng; Khuong An Nguyen; Zhiyuan Luo

An analysis of the properties and the performance of WiFi RTT for indoor positioning in non-line-of-sight environments

Research output: Contribution to conference › Paper › peer-review

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Abstract

Indoor positioning system based on WiFi Round-Trip Time (RTT) measurement is believed to deliver sub-metre level accuracy with trilateration, under ideal indoor conditions. However, the performance of WiFi RTT positioning in complex, non-line-of-sight environments re-mains a research challenge.To this end, this paper investigates the properties of WiFi RTT in several real-world indoor environments on heterogeneous smartphones. We present a large-scale real-world dataset containing both RTT and received signal strength (RSS) signal measures with correct ground-truth labels.Our results indicated that RTT fingerprinting system delivered an accuracy below 0.75 m which was 98% better than RSS fingerprinting and 166% better than RTT trilateration, which failed to deliver sub-metre accuracy as claimed.

Original language	English
Number of pages	17
Publication status	Published - 12 Sept 2022

Keywords

Indoor Positioning
WiFi Round-Trip Time
Non-line-of-sight measure

Access to Document

Manuscript

https://conferences.lfk.lrg.tum.de/lbs2022/

Cite this

@conference{2674a51c3c06491ba0f0435486db716b,

title = "An analysis of the properties and the performance of WiFi RTT for indoor positioning in non-line-of-sight environments",

abstract = "Indoor positioning system based on WiFi Round-Trip Time (RTT) measurement is believed to deliver sub-metre level accuracy with trilateration, under ideal indoor conditions. However, the performance of WiFi RTT positioning in complex, non-line-of-sight environments re-mains a research challenge.To this end, this paper investigates the properties of WiFi RTT in several real-world indoor environments on heterogeneous smartphones. We present a large-scale real-world dataset containing both RTT and received signal strength (RSS) signal measures with correct ground-truth labels.Our results indicated that RTT fingerprinting system delivered an accuracy below 0.75 m which was 98% better than RSS fingerprinting and 166% better than RTT trilateration, which failed to deliver sub-metre accuracy as claimed.",

keywords = "Indoor Positioning, WiFi Round-Trip Time, Non-line-of-sight measure",

author = "Xu Feng and Nguyen, {Khuong An} and Zhiyuan Luo",

note = "17th International Conference on Location Based Services, LBS 2022 ; Conference date: 12-09-2022 Through 14-09-2022",

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TY - CONF

T1 - An analysis of the properties and the performance of WiFi RTT for indoor positioning in non-line-of-sight environments

AU - Feng, Xu

AU - Nguyen, Khuong An

AU - Luo, Zhiyuan

N1 - 17th International Conference on Location Based Services, LBS 2022 ; Conference date: 12-09-2022 Through 14-09-2022

PY - 2022/9/12

Y1 - 2022/9/12

N2 - Indoor positioning system based on WiFi Round-Trip Time (RTT) measurement is believed to deliver sub-metre level accuracy with trilateration, under ideal indoor conditions. However, the performance of WiFi RTT positioning in complex, non-line-of-sight environments re-mains a research challenge.To this end, this paper investigates the properties of WiFi RTT in several real-world indoor environments on heterogeneous smartphones. We present a large-scale real-world dataset containing both RTT and received signal strength (RSS) signal measures with correct ground-truth labels.Our results indicated that RTT fingerprinting system delivered an accuracy below 0.75 m which was 98% better than RSS fingerprinting and 166% better than RTT trilateration, which failed to deliver sub-metre accuracy as claimed.

AB - Indoor positioning system based on WiFi Round-Trip Time (RTT) measurement is believed to deliver sub-metre level accuracy with trilateration, under ideal indoor conditions. However, the performance of WiFi RTT positioning in complex, non-line-of-sight environments re-mains a research challenge.To this end, this paper investigates the properties of WiFi RTT in several real-world indoor environments on heterogeneous smartphones. We present a large-scale real-world dataset containing both RTT and received signal strength (RSS) signal measures with correct ground-truth labels.Our results indicated that RTT fingerprinting system delivered an accuracy below 0.75 m which was 98% better than RSS fingerprinting and 166% better than RTT trilateration, which failed to deliver sub-metre accuracy as claimed.

KW - Indoor Positioning

KW - WiFi Round-Trip Time

KW - Non-line-of-sight measure

M3 - Paper

ER -