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Sensors 2016, 16(11), 1898; doi:10.3390/s16111898

Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting

Intelligent Systems Research Institute, Sungkyunkwan University, Suwon, Gyeonggi-do 440-746, Korea
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Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 15 September 2016 / Revised: 30 October 2016 / Accepted: 5 November 2016 / Published: 11 November 2016
(This article belongs to the Section Sensor Networks)
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Abstract

A method of location fingerprinting based on the Wi-Fi received signal strength (RSS) in an indoor environment is presented. The method aims to overcome the RSS instability due to varying channel disturbances in time by introducing the concept of invariant RSS statistics. The invariant RSS statistics represent here the RSS distributions collected at individual calibration locations under minimal random spatiotemporal disturbances in time. The invariant RSS statistics thus collected serve as the reference pattern classes for fingerprinting. Fingerprinting is carried out at an unknown location by identifying the reference pattern class that maximally supports the spontaneous RSS sensed from individual Wi-Fi sources. A design guideline is also presented as a rule of thumb for estimating the number of Wi-Fi signal sources required to be available for any given number of calibration locations under a certain level of random spatiotemporal disturbances. Experimental results show that the proposed method not only provides 17% higher success rate than conventional ones but also removes the need for recalibration. Furthermore, the resolution is shown finer by 40% with the execution time more than an order of magnitude faster than the conventional methods. These results are also backed up by theoretical analysis. View Full-Text
Keywords: indoor positioning; Wi-Fi fingerprinting; WLAN indoor localization; smartphone sensor; received signal strength (RSS) indoor positioning; Wi-Fi fingerprinting; WLAN indoor localization; smartphone sensor; received signal strength (RSS)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Husen, M.N.; Lee, S. Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting. Sensors 2016, 16, 1898.

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