An adaptive array architecture is described which has improved convergence speed over the conventional Applebaum array when the eigenvalue spread of the input signal covariance matrix is large. The architecture uses N+1 Applebaum adaptive arrays in a two-layer cascaded configuration. The gain constants in the first layer are set so that large interfering sources are quickly nulled, but small interfering sources are suppressed more slowly. Since the first layer removes the large interfering signals, the gain constant for the second layer can be set to a large value to quickly null the smaller interferers. The adaptation time is examined for several combinations of signal levels and array sizes. It is shown that, in many signal environments, the computational requirements for the cascaded array compare favorably with those of conventional sample matrix inversion (SMI) methods for large arrays.<>


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Rapid convergence by cascading Applebaum adaptive arrays


    Beteiligte:
    Ganz, M.W. (Autor:in)


    Erscheinungsdatum :

    1994-04-01


    Format / Umfang :

    922404 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    Rapid Convergence Rate in Adaptive Arrays

    Reed, I.S. / Mallett, J.D. / Brennan, L.E. | IEEE | 1974


    Convergence Properties of Analytical Target Cascading

    Michelena, Nestor / Park, Hyungju / Papalambros, Panos | AIAA | 2002