Global navigation satellite system (GNSS) spoofing attacks pose severe threats to position security. Since the 5G signals are unaffected by GNSS spoofing attacks, they have the potential to provide external assistance to detect GNSS spoofing threats and recover the user equipment (UE)’s authentic position. It can be easily achieved when multiple 5G base stations (BSs) are accessible, as the true position can be directly calculated by using 5G measurements alone. However, in a common situation where only one 5G BS is available, this problem would be difficult. This work aims to detect GNSS spoofing attacks and help the UE recover its authentic position when only one BS is available. First, we extend the innovation-based anomaly detection concept to the GNSS-5G hybrid positioning system for spoofing detection. Then, the fusion extended Kalman filter output model under spoofing attacks is derived and proved mathematically. Based on this, a three-stage authentic position estimation algorithm is proposed. Both simulations and a real field test were implemented. Results illustrate that our method can directly rebuild the actual location of the UE from the spoofed GNSS-5G hybrid positioning result with only one 5G BS.


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    Title :

    GNSS Spoofing Detection and Mitigation With a Single 5G Base Station Aiding


    Contributors:
    Bai, Lu (author) / Sun, Chao (author) / Dempster, Andrew G. (author) / Zhao, Hongbo (author) / Feng, Wenquan (author)


    Publication date :

    2024-08-01


    Size :

    6081907 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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