We consider two-dimensional (2-D) nonparametric complex spectral estimation (with its 1-D counterpart as a special case) of data matrices with missing samples occurring in arbitrary patterns. Previously, the missing amplitude and phase estimation-expectation maximization (MAPES-EM) algorithms were developed for the general 1-D missing-data problem and shown to have excellent spectral estimation performance. In this correspondence, we present 2-D extensions of MAPES-EM and develop another 2-D MAPES algorithm, referred to as MAPES-CM, which solves a maximum likelihood problem iteratively via cyclic maximization (CM). Compared with MAPES-EM, MAPES-CM has similar spectral estimation performance but is computationally much more efficient, which is especially important for long data sequences and 2-D applications such as synthetic aperture radar (SAR) imaging.


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    Titel :

    Two-dimensional nonparametric spectral analysis in missing data case


    Beteiligte:
    Yanwei Wang (Autor:in) / Stoica, P. (Autor:in) / Jian Li (Autor:in)


    Erscheinungsdatum :

    01.10.2007


    Format / Umfang :

    2561241 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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