Jamming attacks pose a serious threat to global navigation satellite system single-antenna receivers, and extensive technologies have been developed to mitigate some specific jamming types. In real environments, an adaptive jamming countermeasure should be developed to mitigate the jamming signals due to the lack of knowledge on the existence and types of potential jamming attacks. We propose an integrated method capable of coping with various jamming signals efficiently for single-antenna receivers. The integrated method is implemented by a stand-alone module before the signal processing stage to detect, classify, filter, and monitor varying jamming attacks. In this method, the differential cumulative energy spectrum power metric that describes the spectrum characteristics of the received signals is developed to detect and identify jamming attacks. The adaptive notch filter (ANF) is then improved to filter and dynamically monitor jamming environments through the aid of switchable iteration factors and a check unit. The iteration factors are adjusted for adapting ANF to the identified jamming types. The check unit monitors the state of jamming circumstances and updates the antijamming method by evaluating the ANF performance. The proposed method is tested by semiphysical simulations of common jamming circumstances. It can cope with common jamming attacks with over 21 dB of jamming-to-noise ratio. The $C/{{N}_0}$ improvement is up to 19 dB·Hz, which can be 4.6 dB·Hz higher than the conventional ANF. Moreover, with the proposed method, mitigation performance under varying jamming cases is improved effectively.


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    Title :

    Adaptive Jamming Mitigation in Single-Antenna Receivers With Spectral Analysis and Switchable Filtering


    Contributors:
    Ding, Mengyu (author) / Chen, Wu (author) / Weng, Duojie (author) / Mi, Xiaolong (author)


    Publication date :

    2024-10-01


    Size :

    3534453 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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