Wifi fingerprinting localization for intelligent vehicles in car park

In this paper, a novel method of WiFi fingerprinting for localizing intelligent vehicles in GPS-denied area, such as car parks, is proposed. Although the method itself is a popular approach for indoor localization application, adapting it to the speed of vehicles requires different treatment. By dep...

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Bibliographic Details
Published in2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) pp. 1 - 6
Main Authors Nguyen, Dinh-Van, Charette, Raoul De, Nashashibi, Fawzi, Dao, Trung-Kien, Castelli, Eric
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2018
Subjects
Automobiles
component
Ensemble Neural Network
Fingerprint recognition
Global Positioning System
Indoor localization
Intelligent vehicles
Neural networks
Particle Filter
Particle filters
Sensor Fusion
WiFi Fingerprinting
Wireless fidelity
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Summary:In this paper, a novel method of WiFi fingerprinting for localizing intelligent vehicles in GPS-denied area, such as car parks, is proposed. Although the method itself is a popular approach for indoor localization application, adapting it to the speed of vehicles requires different treatment. By deploying an ensemble neural network for fingerprinting classification, the method shows a reasonable localization precision at car park speed. Furthermore, a Gaussian Mixture Model (GMM) Particle Filter is applied to increase localization frequency as well as accuracy. Experiments show promising results with average localization error of 0.6m.
ISSN:2471-917X
DOI:10.1109/IPIN.2018.8626578