We examine large-sample properties of the maximum- likelihood estimator (MLE) in the vicinity of points where the Fisher information measure (FIM) equals zero. Under mild regularity conditions the MLE is asymptotically efficient and therefore lower bounded by the Cramer-Rao lower bound (CRLB) [5], which diverges for such points. When a linear sensor array is used for angle-of-arrival (AOA) estimation, the CRLB diverges as the AOA approaches pi/2. We provide new results characterizing the MLE performance in the AOA problem.


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    Title :

    Estimation near "Zero Information" points: angle-of-arrival near the endfire


    Contributors:
    Bashan, E. (author) / Weiss, A.J. (author) / Bar-Shalom, Y. (author)


    Publication date :

    2007-10-01


    Size :

    1842170 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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