In many applications, the practical usefulness of adaptive arrays is limited by their convergence rate. The adaptively controlled weights in these systems must change at a rate equal to or greater than the rate of change of the external noise field (e.g., due to scanning in a radar if step scan is not used). This convergence rate problem is most severe in adaptive systems with a large number of degrees of adaptivity and in situations where the eigenvalues of the noise covariance matrix are widely different. A direct method of adaptive weight computation, based on a sample covariance matrix of the noise field, has been found to provide very rapid convergence in all cases, i.e., independent of the eigenvalue distribution. A theory has been developed, based on earlier work by Goodman, which predicts the achievable convergence rate with this technique, and has been verified by simulation.


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    Title :

    Rapid Convergence Rate in Adaptive Arrays


    Contributors:
    Reed, I.S. (author) / Mallett, J.D. (author) / Brennan, L.E. (author)

    Published in:

    Publication date :

    1974-11-01


    Size :

    2324817 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English