A general non-asymptotic theoretical analysis is developed for fingerprinting localization system designs. Based on this analysis, hybrid fingerprinting and propagation-based methods are proposed using 5G-like received signal strength (RSS), time of arrival (TOA), and direction of arrival (DOA) measurements which have been a focus in recent 3GPP Rel 16 and Rel 17 positioning activities. The proposed hybrid methods have the flexibility and robustness of fingerprinting methods in dealing with none-line-of-sight (NLOS) problem while inheriting the efficiency and accuracy of propagation-based methods in 3-D localization. Specifically, a ray extension technique is developed as the propagation-based method. Then the ray extension is combined with two fingerprinting methods, the conventional weighted k-nearest neighbors (WKNN) and the proposed optimal WKNN (OWKNN), in order to remedy the geometrical deficiency in fingerprinting methods. Based on the non-asymptotic study, the proposed hybrid methods are guaranteed to outperform the fingerprinting methods without ray extension. Verification of the proposed methods is performed in a large none-line-of-sight (NLOS) urban San Jose region using simulation data provided by a previously developed super-efficient ray launcher.


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    Titel :

    Hybrid Fingerprinting and Ray Extension Localization in NLOS Regions


    Beteiligte:
    Li, Jun (Autor:in) / Lu, I-Tai (Autor:in) / Lu, Jonathan S. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.12.2022


    Format / Umfang :

    1336264 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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