淡江大學機構典藏:Item 987654321/60804
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/60804


    Title: Adaptive Linearly Constrained Inverse QRD-RLS Beamforming Algorithm for Moving Jammers Suppression
    Authors: 陳巽璋;Chang, C.Y.
    Contributors: 淡江大學電機工程學系
    Date: 2002-08-01
    Issue Date: 2011-10-15 00:54:25 (UTC+8)
    Abstract: A general, linearly constrained (LC) recursive least squares (RLS) array-beamforming algorithm, based on an inverse QR decomposition, is developed for suppressing moving jammers efficiently. In fact, by using the inverse QR decomposition-recursive least squares (QRD-RLS) algorithm approach, the least-squares (LS) weight vector can be computed without back substitution and is suitable for implementation using a systolic array to achieve fast convergence and good numerical properties. The merits of this new constrained algorithm are verified by evaluating the performance, in terms of the learning curve, to investigate the convergence property and numerical efficiency, and the output signal-to-interference-and-noise ratio. We show that our proposed algorithm outperforms the conventional linearly constrained LMS (LCLMS) algorithm, and the one using the fast linear constrained RLS algorithm and its modified version.
    Relation: IEEE Trans. on Antennas and Propagation 50(8), pp.1138-1150
    DOI: 10.1109/TAP.2002.801276
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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