Herein derived are the lower and upper bounds for the number of linearly independent (2Q)th-order virtual steering vectors of an array of electromagnetic vector-sensors, with Q being any positive integer over one. These bounds help determine the number of non-Gaussian signals whose directions-of-arrival (DOAs) can be uniquely identified from (2Q)th-order statistics data. The derived lower bounds increase with Q, whereas the derived upper bounds often fall below the maximum number of virtual sensors achievable from (2Q)th-order statistics manipulation. These bounds are independent of the permutation of the (2Q)th-order statistics entries in the higher order cumulant matrix that has a similar algebraic structure of the classical covariance matrix used in the second-order subspace-based direction-finding algorithms.


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    Title :

    Virtual-manifold ambiguity in HOS-based direction-finding with electromagnetic vector-sensors


    Contributors:
    Yougen Xu, (author) / Zhiwen Liu, (author) / Wong, K.T. (author) / Jinliang Cao, (author)


    Publication date :

    2008-10-01


    Size :

    4087055 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English