A new compressive-sensing (CS)-based electronic warfare (EW) receiver is designed to estimate the angle-Doppler of adversary targets whose waveforms are unknown. The proposed EW receiver uses a sparse Bayesian learning (SBL) framework, which is blind in the sense that the knowledge of the sparsity basis is not available. Furthermore, a pruning mechanism is proposed to reduce the computational cost and improve convergence speed of the blind-SBL. The convergence of the proposed method is analytically proved.


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    Titel :

    Blind Compressive-Sensing-Based Electronic Warfare Receiver


    Beteiligte:
    Salari, Soheil (Autor:in) / Il-Min Kim (Autor:in) / Chan, Francois (Autor:in) / Rajan, Sreeraman (Autor:in)


    Erscheinungsdatum :

    01.08.2017


    Format / Umfang :

    1200121 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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