Airborne weather radars are used by pilots to identify areas containing significant precipitation, turbulence, and wind shear on the flight path. The different atmospheric hazards can be determined by airborne weather radar using the spectral moments of radar echoes. The pulse pair processing method and the FFT based method are the most widely used spectral moments estimators. However, the performance of these method is poor under low SNR conditions as it is a nonparametric method. A parametric spectral moments estimation method is proposed based on subspace analysis of the covariance matrix of the echoes with Gaussian-shaped spectrum. A fast algorithm for this method is also implemented for demonstration, in which the 2D-search problem is decomposed into two 1D-search routines. The numerical analysis verifies that the presented method functions effectively in low SNR scenario.


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    Titel :

    Low complexity spectral moments estimator under low SNR condition


    Beteiligte:
    Xiaoguang Lu (Autor:in) / Zhe Zhang (Autor:in) / Ping Han (Autor:in)


    Erscheinungsdatum :

    01.04.2016


    Format / Umfang :

    1010368 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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