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An efficient adaptive algorithm for the direction-of-arrival (DOA) estimation utilizing the solution of extreme eigenvalue problem

机译:一种利用极端特征值问题求解的有效到达方向(DOA)估计自适应算法

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摘要

The authors introduce an alternative method for solving the extreme eigenvalue problem for DOA estimation. The proposed technique utilizes the conjugate gradient method (CGM) for iteratively and efficiently finding one of the noise eigenvectors which corresponds to the smallest eigenvalue of the autocovariance matrix which is full complex-valued semidefinite Hermitian. When the proposed minimum eigenvalue searching (MES) method is utilized, only one noise eigenvector which corresponds to the smallest eigenvalue is computed. In addition to circumventing the need for a separate routine, the MES method can estimate the DOA of fully coherent signals without including the detection procedure under the assumption that the number of unknowns involved in the procedure is larger than the actual number of signals. The authors also provide a suggestion for removing the pseudopeaks appearing in the spatial spectrum due to the large number of antenna elements.
机译:作者介绍了一种用于求解DOA估计的极端特征值问题的替代方法。所提出的技术利用共轭梯度法(CGM)迭代并有效地找到了噪声特征向量之一,该噪声特征向量与自协方差矩阵的最小特征值相对应,该特征值是全复数值半定Hermitian。当使用所提出的最小特征值搜索(MES)方法时,仅计算对应于最小特征值的一个噪声特征向量。除了避免需要单独的例程外,MES方法还可以估计完全相干信号的DOA,而无需考虑检测过程,前提是该过程中涉及的未知数大于信号的实际数目。作者还提出了消除由于大量天线元件而出现在空间频谱中的伪峰的建议。

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