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基于SVD的特征空间波束合成器 被引量:3

Eigenspace beamforming based on SVD
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摘要 针对特征空间波束合成器,采用对数据矩阵进行奇异值分解,利用奇异值和奇异值矢量计算最优权矢量,完成波束合成。该方法不仅完成特征空间降维作用,同时可以避免对阵列协方差矩阵的估计,减少估计运算量和估计误差。实现的主要步骤包括了奇异值分解的数值计算,信源数估计,期望信号波达方向估计和权值求解几个方面。计算机仿真证明,新算法可以正确实现波束合成,提高系统增益。 By SVD of data matrix and optimum weight vector choose using the singular values and singular vectors, the eigenspace beamforming is carried out in this paper. The algorithm reduces the dimension of matrix computation and avoids the estimation of array covariance matrix. So the computation load and estimation error decrease heavily. The algorithm consists of SVD, signals' number and DOA estimation, and weight vector solution. The computer simulation shows that the proposed algorithm can form the beam and improve the array gain.
出处 《电波科学学报》 EI CSCD 北大核心 2008年第6期1194-1198,1208,共6页 Chinese Journal of Radio Science
基金 国家自然科学基金资助项目(No.60672097) 重庆市自然科学基金资助项目(2008BB2310)
关键词 波束合成 特征空间 奇异值分解 beamforming eigensapce SVD
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参考文献9

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同被引文献51

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