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基于特征空间重构的子阵级ADBF方法 被引量:1

ADBF algorithm at subarray level based on eigenspace reconstruction
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摘要 为实现大型阵列天线子阵级自适应数字波束形成,提出了一种基于阵列特征空间重构的方法。对子阵协方差矩阵进行奇异值分解,分离出信号、干扰与噪声子空间对应的特征值以及特征向量,并对特征子空间重新分配,重构阵列特征空间,完成子阵级ADBF。与常规方法相比,该方法能够消除子阵级输出噪声功率不一致造成的阵列方向图畸变,减小协方差矩阵估计误差的影响。理论分析与仿真结果表明,该方法在子阵级波束形成以及抗干扰接收等方面具有优良性能。 An adaptive digital beamforming algorithm at subarray level based on eigenspace reconstruction is proposed for large array antenna. With the SVD of covariance matrix at subarray, eigenvalue and eigenvalue vector at signal jamming and noise subspace are decomposed. And then the eigenspace is reconstructed, which can be used to carry out the adaptive beamformin more effectively. Compared with traditional methods, the present method could avoid the influence of unequal noise power out of each subarray, and also reduce the estimation error of covariance matrix. Theoretical analyses and simulation results show that this ADBF algorithm has excellent performance at adaptive beamforming and anti-jamming receive.
出处 《航天电子对抗》 2014年第3期17-21,共5页 Aerospace Electronic Warfare
关键词 子阵 特征空间 自适应数字波束形成 奇异值分解 subarray eigenspace ADBF SVD
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