Enhancing Passive WiFi Device Localization Through Packet Timing Analysis

This article presents an innovative timing-based localization method aimed at determining the positions of active WiFi devices through passive reception. The method involves capturing and analyzing the timing of over-the-air WiFi packets: request-to-send (RTS), clear-to-send (CTS), data (DATA), and...

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Main Authors: Omar Dhawahir, Murat Torlak
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of Instrumentation and Measurement
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10817509/
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author Omar Dhawahir
Murat Torlak
author_facet Omar Dhawahir
Murat Torlak
author_sort Omar Dhawahir
collection DOAJ
description This article presents an innovative timing-based localization method aimed at determining the positions of active WiFi devices through passive reception. The method involves capturing and analyzing the timing of over-the-air WiFi packets: request-to-send (RTS), clear-to-send (CTS), data (DATA), and acknowledgment (ACK) packets exchanged between WiFi routers and clients. The accuracy of round-trip time (RTT) estimation, crucial for distance calculation, can be affected by factors, such as clock variations between devices and, notably, the short interframe space (SIFS) time setting in the WiFi protocol. Despite SIFS time aiming to ensure a consistent interval between DATA and ACK frame transmissions, IEEE 802.11 standards permit up to a 10% variation in SIFS time. When combined with device-level disparities and environmental fluctuations, individual RTT measurements may not reliably estimate distances. In this study, we employ statistical clustering techniques, specifically k-means clustering, to enhance RTT estimation by refining coarse- and fine-timing estimates. Each captured packet pair, i.e., (DATA/ACK), is assigned to the cluster with the most similar coarse and fine RTT characteristics. Subsequently, the properties of the identified cluster (e.g., coarse RTT/fine RTT) are utilized as a more precise RTT estimate for localization computations. Simulations and experiments conducted under diverse multipath conditions demonstrate the algorithm’s accuracy in 2-D positioning, achieving an average accuracy of as low as 0.24 m in simulations and 1.18 m in experiments when the Wi-Fi router and device are separated by distances of up to 18 m. The proposed method offers a robust approach for accurate passive Wi-Fi positioning, highlighting its potential for real-world applications.
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spelling doaj-art-dc2e5c2f07fa46d4a3efaed854852b222025-01-25T00:03:51ZengIEEEIEEE Open Journal of Instrumentation and Measurement2768-72362025-01-01411310.1109/OJIM.2024.352234510817509Enhancing Passive WiFi Device Localization Through Packet Timing AnalysisOmar Dhawahir0https://orcid.org/0009-0002-4035-3049Murat Torlak1https://orcid.org/0000-0001-7229-1765Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USADepartment of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USAThis article presents an innovative timing-based localization method aimed at determining the positions of active WiFi devices through passive reception. The method involves capturing and analyzing the timing of over-the-air WiFi packets: request-to-send (RTS), clear-to-send (CTS), data (DATA), and acknowledgment (ACK) packets exchanged between WiFi routers and clients. The accuracy of round-trip time (RTT) estimation, crucial for distance calculation, can be affected by factors, such as clock variations between devices and, notably, the short interframe space (SIFS) time setting in the WiFi protocol. Despite SIFS time aiming to ensure a consistent interval between DATA and ACK frame transmissions, IEEE 802.11 standards permit up to a 10% variation in SIFS time. When combined with device-level disparities and environmental fluctuations, individual RTT measurements may not reliably estimate distances. In this study, we employ statistical clustering techniques, specifically k-means clustering, to enhance RTT estimation by refining coarse- and fine-timing estimates. Each captured packet pair, i.e., (DATA/ACK), is assigned to the cluster with the most similar coarse and fine RTT characteristics. Subsequently, the properties of the identified cluster (e.g., coarse RTT/fine RTT) are utilized as a more precise RTT estimate for localization computations. Simulations and experiments conducted under diverse multipath conditions demonstrate the algorithm’s accuracy in 2-D positioning, achieving an average accuracy of as low as 0.24 m in simulations and 1.18 m in experiments when the Wi-Fi router and device are separated by distances of up to 18 m. The proposed method offers a robust approach for accurate passive Wi-Fi positioning, highlighting its potential for real-world applications.https://ieeexplore.ieee.org/document/10817509/Frame time of arrival (FTA)IEEE 802.11passive localizationpositioninground-trip time (RTT)symbol timing offset (STO)
spellingShingle Omar Dhawahir
Murat Torlak
Enhancing Passive WiFi Device Localization Through Packet Timing Analysis
IEEE Open Journal of Instrumentation and Measurement
Frame time of arrival (FTA)
IEEE 802.11
passive localization
positioning
round-trip time (RTT)
symbol timing offset (STO)
title Enhancing Passive WiFi Device Localization Through Packet Timing Analysis
title_full Enhancing Passive WiFi Device Localization Through Packet Timing Analysis
title_fullStr Enhancing Passive WiFi Device Localization Through Packet Timing Analysis
title_full_unstemmed Enhancing Passive WiFi Device Localization Through Packet Timing Analysis
title_short Enhancing Passive WiFi Device Localization Through Packet Timing Analysis
title_sort enhancing passive wifi device localization through packet timing analysis
topic Frame time of arrival (FTA)
IEEE 802.11
passive localization
positioning
round-trip time (RTT)
symbol timing offset (STO)
url https://ieeexplore.ieee.org/document/10817509/
work_keys_str_mv AT omardhawahir enhancingpassivewifidevicelocalizationthroughpackettiminganalysis
AT murattorlak enhancingpassivewifidevicelocalizationthroughpackettiminganalysis