Precise positioning has become one core topic in wireless communications by facilitating candidate techniques of beyond 5G and 6G. Nevertheless, most existing positioning algorithms, categorized into geometry-driven and data-driven approaches, fail to simultaneously fulfill diversified requirements for practical use, e.g., accuracy, real-time operation, scalability, maintenance, etc. This article aims at introducing a new principle, called combinatorial data augmentation (CDA), a catalyst for tightly integrating geometry and data-driven approaches. We first explain the concept of CDA and its critical advantages over the two standalone approaches, followed by validating its effectiveness by field experiments with WiFi round-trip time and inertial measurement units.


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    Titel :

    Combinatorial Data Augmentation for Real-Time Indoor Positioning: Concepts and Experiments


    Beteiligte:
    Yu, Seung Min (Autor:in) / Park, Jihong (Autor:in) / Ko, Seung-Woo (Autor:in)


    Erscheinungsdatum :

    01.06.2022


    Format / Umfang :

    1072854 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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