For time-varying clutter suppression in passive bistatic radar (PBR) systems, some existing clutter suppression algorithms, belonging to the time-domain filter (TDF) or the frequency-domain filter (FDF), will suffer from performance degradation in the presence of fractional-order range clutter or fractional-order Doppler clutter, respectively. Additionally, some FDF-based clutter cancellation algorithms with subband operation will produce undesired periodic peaks in the range domain, which is analyzed for the first time in this article. To overcome the above limitations, an advanced extensive cancellation algorithm based on overlapping subband (ECA-OS) is developed. Initially, the clutter subspace with Doppler frequency is constructed in the time domain with the reference signal, where the clutter cancellation order in the range domain is constrained to one-dimension. Subsequently, the echo signal and constructed clutter subspace are transformed to frequency-domain, followed by subband operation. Finally, in conjunction with the least squares criterion, the weight coefficients of time-varying clutter are estimated with an overlapping subband, and the clutter cancellation is implemented in each subband. Attributed to the above operations, both the fractional-order Doppler clutter and fractional-order range clutter are suppressed by the proposed ECA-OS with low computational complexity. In addition, by overlapping subband operation to introduce an additional degree of freedom (DOF), the proposed algorithm can avoid the generation of periodic peaks in the range domain. The effectiveness of proposed ECA-OS is verified by theoretical derivations, simulations, and measured data.


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    Titel :

    An Extensive Cancellation Algorithm via Overlapping Subband for Time-Varying Clutter Suppression in Passive Bistatic Radar


    Beteiligte:
    Sui, Jinxin (Autor:in) / Wang, Jun (Autor:in) / Gao, Jie (Autor:in) / Fan, Xiaoyan (Autor:in)


    Erscheinungsdatum :

    2024-08-01


    Format / Umfang :

    6118950 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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