Passive Indoor Localization with WiFi Fingerprints
Minh Tu Hoang, Brosnan Yuen, Kai Ren, Ahmed Elmoogy, Xiaodai Dong, Tao Lu, Hung Le Nguyen Robert Westendorp, and Kishore Reddy Tarimala

TL;DR
This paper introduces a passive WiFi indoor localization method that uses signals received by routers instead of mobile devices, eliminating the need for software installation on phones and achieving high accuracy through various algorithms.
Contribution
It presents a novel passive localization approach using router-received signals and flow control signals to improve data sufficiency, with extensive experimental validation.
Findings
Achieves 0.8 m average error during active transmission
Achieves 1.5 m average error during passive reception
Demonstrates effectiveness across various phone models and locations
Abstract
This paper proposes passive WiFi indoor localization. Instead of using WiFi signals received by mobile devices as fingerprints, we use signals received by routers to locate the mobile carrier. Consequently, software installation on the mobile device is not required. To resolve the data insufficiency problem, flow control signals such as request to send (RTS) and clear to send (CTS) are utilized. In our model, received signal strength indicator (RSSI) and channel state information (CSI) are used as fingerprints for several algorithms, including deterministic, probabilistic and neural networks localization algorithms. We further investigated localization algorithms performance through extensive on-site experiments with various models of phones at hundreds of testing locations. We demonstrate that our passive scheme achieves an average localization error of 0.8 m when the phone is actively…
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Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Underwater Vehicles and Communication Systems · Speech and Audio Processing
