Range-dependent clutter suppression is a challenging problem in nonsidelooking, bistatic, and conformal antenna array airborne radar, especially in the presence of range ambiguity. Superimposed stepped frequency (SSF) radar employs a small frequency increment across the stepped signals in each pulse, which introduces a dimension related to slant range. In this article, an airborne radar framework is established, which takes SSF signal as the transmit waveform. Thus, a two-stage adaptive clutter suppression method is proposed, which utilizes the degrees of freedom in range, space, and time domains provided by airborne SSF radar. In the first stage, the secondary range dependence compensation approach is adopted to distinguish the clutter of each range region in the carrier frequency domain. Then, a target-free covariance matrix is estimated by the compensated data, and the covariance matrix is used for the range-ambiguous clutter separation in the carrier frequency domain. Thus, the space-time snapshot of each range region can be extracted. In the second stage, a clutter segmentation processing method is devised for residual clutter suppression. For the near-range unambiguous clutter, the traditional clutter compensation approach is applied to further align the spectrum distribution of clutter, while the conventional space-time adaptive processing is utilized to suppress far-range clutter directly. Since the proposed method takes full advantage of the range dimension and the two stages of adaptive processing are data-dependent, excellent clutter suppression performance can be obtained. The proposed method can also extract the real range of the target since each range region is processed separately. Simulation results demonstrate the effectiveness of the proposed method.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Range-Dependent Ambiguous Clutter Suppression for Airborne SSF-STAP Radar


    Beteiligte:
    Chen, Wei (Autor:in) / Xie, Wenchong (Autor:in) / Wang, Yongliang (Autor:in)


    Erscheinungsdatum :

    2022-04-01


    Format / Umfang :

    4031503 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch