Enhancing WiFi RSS fingerprint positioning accuracy: Lobe-forming in radiation pattern enabled by an air-gap

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    1 Citation (Scopus)

    Abstract

    We propose a physical arrangement consisting of a 2.4 GHz WiFi radio, and high attenuation surfaces with an air-gap in-between, to delimit a fingerprinting region. We show by simulations, and field measurements, that such arrangement allows to form a characteristic lobe in the radiation pattern after the gap, which is characterized by an abrupt change in the Received Signal Strengths (RSSs) along the direction parallel to the surfaces. From measured RSS samples, we construct, to aid our analysis, an equation that approximates the radiation pattern as a continuous RSS radio map, using symbolic regression. Finally, we observe the positioning performance of this arrangement, performing RSS fingerprint pattern matching with a Neural Network. Results are compared to the positioning accuracy that would be obtained by using an omnidirectional radiation pattern antenna. We conclude that, the abrupt change in RSSs obtained with this arrangement, translates into a better positioning accuracy, close and along a direction parallel to the surfaces.

    Original languageEnglish
    Title of host publication2019 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2019
    PublisherIEEE Institute of Electrical and Electronic Engineers
    ISBN (Electronic)978-1-7281-1788-1
    ISBN (Print)978-1-7281-1789-8
    DOIs
    Publication statusPublished - Sep 2019
    MoE publication typeA4 Article in a conference publication
    Event2019 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2019 - Pisa, Italy
    Duration: 30 Sep 20193 Oct 2019

    Conference

    Conference2019 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2019
    CountryItaly
    CityPisa
    Period30/09/193/10/19

    Keywords

    • Accuracy
    • Air-gap
    • Indoor positioning
    • Neural Network
    • Proximity Sensor
    • Radiation Pattern
    • RSS fingerprinting
    • Symbolic Regression
    • WiFi
    • OtaNano

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