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An efficient reduce-rank algorithm based on joint iterative optimization for planar array

机译:基于联合迭代优化的平面阵列高效降秩算法

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Reducing rank plays an important role in the adaptive array process, especially two dimensional (2D) planar array system with large number of antenna elements. A new reduced-rank algorithm for planar adaptive arrays is proposed in this paper. The algorithm consists of a joint iterative optimization of the adaptive weights and the reduced-rank matrix which does not need to be deliberately structured. Minimum variance (MV) expression for the algorithm is described and relative NLMS implementation is developed. The proposed algorithm can save the computation cost for large 2D planar adaptive arrays. Simulations results illustrate the effectiveness of this algorithm.
机译:降低秩在自适应阵列过程中起着重要作用,尤其是具有大量天线元件的二维(2D)平面阵列系统。提出了一种新的平面自适应阵列降秩算法。该算法由自适应权重和降阶矩阵的联合迭代优化组成,不需要故意构造。描述了该算法的最小方差(MV)表达式,并开发了相关的NLMS实现。所提出的算法可以节省大型二维平面自适应阵列的计算成本。仿真结果说明了该算法的有效性。

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