Smartphone-based Indoor Positioning Using Wi-Fi Fine Timing Measurement Protocol

Research output: ThesisMaster's thesisTheses

Abstract

Location-based services have grown popular since GPS and other satellite navigation systems became available for consumers. However, because satellite signals are absent inside buildings, other means of positioning need to be used to enable similar services as outdoors. In the case of mobile phones, Wi-Fi received signal strength has been a widely studied option for positioning. Indoor environment is challenging, because the readings have significant fluctuation due to interference from walls, furniture and people. Fine Timing Measurement (FTM) is a new addition to the IEEE 802.11 WLAN standard. It provides Wi-Fi positioning that relies on the time of flight of the signal instead of its received strength. Time of flight information is supposed to be more reliable compared to signal strength, providing more accurate distance estimates to be used in positioning. FTM is claimed to provide meter-level positioning accuracy.
In this thesis, the FTM protocol is introduced, and a smartphone positioning system is implemented. The system includes two alternative Android applications for recording and visualizing FTM data, and two algorithms for calculating position estimates. With an FTM-enabled smartphone and Wi-Fi access points, the positioning accuracy of FTM is evaluated with field measurements in two different office environments. Using an Unscented Kalman Filter algorithm, mean positioning error of 0.72 meters was achieved in a large, open room. In a more scattered AP constellation across multiple rooms, the mean error was 2.07 meters. The results show that meter-level positioning accuracy is possible with FTM, although here it was achieved with favourable AP placements around a single room. In the more realistic setting, room-level accuracy was achieved.
Original languageEnglish
QualificationMaster Degree
Awarding Institution
  • University of Turku
Supervisors/Advisors
  • Horsmanheimo, Seppo, Advisor
  • Nigussie, Ethiopia, Supervisor, External person
  • Thanigaivelan, Nanda, Supervisor, External person
Award date30 Sep 2019
Publisher
Publication statusPublished - 30 Sep 2019
MoE publication typeG2 Master's thesis, polytechnic Master's thesis

Fingerprint

Wi-Fi
Smartphones
Network protocols
Satellites
Location based services
Navigation systems
Wireless local area networks (WLAN)
Mobile phones
Kalman filters
Global positioning system

Keywords

  • Indoor positioning
  • Fine Timing Measurement
  • FTM
  • WLAN
  • Kalman filter
  • Android
  • UKF

Cite this

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title = "Smartphone-based Indoor Positioning Using Wi-Fi Fine Timing Measurement Protocol",
abstract = "Location-based services have grown popular since GPS and other satellite navigation systems became available for consumers. However, because satellite signals are absent inside buildings, other means of positioning need to be used to enable similar services as outdoors. In the case of mobile phones, Wi-Fi received signal strength has been a widely studied option for positioning. Indoor environment is challenging, because the readings have significant fluctuation due to interference from walls, furniture and people. Fine Timing Measurement (FTM) is a new addition to the IEEE 802.11 WLAN standard. It provides Wi-Fi positioning that relies on the time of flight of the signal instead of its received strength. Time of flight information is supposed to be more reliable compared to signal strength, providing more accurate distance estimates to be used in positioning. FTM is claimed to provide meter-level positioning accuracy. In this thesis, the FTM protocol is introduced, and a smartphone positioning system is implemented. The system includes two alternative Android applications for recording and visualizing FTM data, and two algorithms for calculating position estimates. With an FTM-enabled smartphone and Wi-Fi access points, the positioning accuracy of FTM is evaluated with field measurements in two different office environments. Using an Unscented Kalman Filter algorithm, mean positioning error of 0.72 meters was achieved in a large, open room. In a more scattered AP constellation across multiple rooms, the mean error was 2.07 meters. The results show that meter-level positioning accuracy is possible with FTM, although here it was achieved with favourable AP placements around a single room. In the more realistic setting, room-level accuracy was achieved.",
keywords = "Indoor positioning, Fine Timing Measurement, FTM, WLAN, Kalman filter, Android, UKF",
author = "Sami Huilla",
year = "2019",
month = "9",
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language = "English",
publisher = "University of Turku",
address = "Finland",
school = "University of Turku",

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Smartphone-based Indoor Positioning Using Wi-Fi Fine Timing Measurement Protocol. / Huilla, Sami.

University of Turku, 2019. 69 p.

Research output: ThesisMaster's thesisTheses

TY - THES

T1 - Smartphone-based Indoor Positioning Using Wi-Fi Fine Timing Measurement Protocol

AU - Huilla, Sami

PY - 2019/9/30

Y1 - 2019/9/30

N2 - Location-based services have grown popular since GPS and other satellite navigation systems became available for consumers. However, because satellite signals are absent inside buildings, other means of positioning need to be used to enable similar services as outdoors. In the case of mobile phones, Wi-Fi received signal strength has been a widely studied option for positioning. Indoor environment is challenging, because the readings have significant fluctuation due to interference from walls, furniture and people. Fine Timing Measurement (FTM) is a new addition to the IEEE 802.11 WLAN standard. It provides Wi-Fi positioning that relies on the time of flight of the signal instead of its received strength. Time of flight information is supposed to be more reliable compared to signal strength, providing more accurate distance estimates to be used in positioning. FTM is claimed to provide meter-level positioning accuracy. In this thesis, the FTM protocol is introduced, and a smartphone positioning system is implemented. The system includes two alternative Android applications for recording and visualizing FTM data, and two algorithms for calculating position estimates. With an FTM-enabled smartphone and Wi-Fi access points, the positioning accuracy of FTM is evaluated with field measurements in two different office environments. Using an Unscented Kalman Filter algorithm, mean positioning error of 0.72 meters was achieved in a large, open room. In a more scattered AP constellation across multiple rooms, the mean error was 2.07 meters. The results show that meter-level positioning accuracy is possible with FTM, although here it was achieved with favourable AP placements around a single room. In the more realistic setting, room-level accuracy was achieved.

AB - Location-based services have grown popular since GPS and other satellite navigation systems became available for consumers. However, because satellite signals are absent inside buildings, other means of positioning need to be used to enable similar services as outdoors. In the case of mobile phones, Wi-Fi received signal strength has been a widely studied option for positioning. Indoor environment is challenging, because the readings have significant fluctuation due to interference from walls, furniture and people. Fine Timing Measurement (FTM) is a new addition to the IEEE 802.11 WLAN standard. It provides Wi-Fi positioning that relies on the time of flight of the signal instead of its received strength. Time of flight information is supposed to be more reliable compared to signal strength, providing more accurate distance estimates to be used in positioning. FTM is claimed to provide meter-level positioning accuracy. In this thesis, the FTM protocol is introduced, and a smartphone positioning system is implemented. The system includes two alternative Android applications for recording and visualizing FTM data, and two algorithms for calculating position estimates. With an FTM-enabled smartphone and Wi-Fi access points, the positioning accuracy of FTM is evaluated with field measurements in two different office environments. Using an Unscented Kalman Filter algorithm, mean positioning error of 0.72 meters was achieved in a large, open room. In a more scattered AP constellation across multiple rooms, the mean error was 2.07 meters. The results show that meter-level positioning accuracy is possible with FTM, although here it was achieved with favourable AP placements around a single room. In the more realistic setting, room-level accuracy was achieved.

KW - Indoor positioning

KW - Fine Timing Measurement

KW - FTM

KW - WLAN

KW - Kalman filter

KW - Android

KW - UKF

M3 - Master's thesis

PB - University of Turku

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