期刊文献+

运用增广矩阵束方法稀布优化平面阵 被引量:2

Sparse antenna array synthesis using matrix enhancement and matrix pencil
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摘要 基于增广矩阵束方法(Matrix Enhancement and Matrix Pencil,MEMP),以使用尽可能少的阵元逼近期望的方向图为目标,提出了一种求解阵元位置和设计激励幅度的新方法.首先对期望平面阵的方向图进行采样得到离散的数据集,再构造增广矩阵,对此增广矩阵进行奇异值分解(Singular Value Decomposition,SVD),确定逼近期望方向图所需的最小阵元数目;基于广义特征值分解求解两组特征值,并根据类基于旋转不变技术的信号参数估计(Estimating Signal Parameters Via RotationalInvariance Techniques,ESPRIT)对这两组特值配对;在最小二乘准则下求解稀布面阵的阵元位置和激励.仿真试验验证了该方法在稀布平面阵优化问题中的高效性和数值精度. For the purpose of using as few elements as possible to form a desired pattern, a new method based on matrix enhancement and matrix pencil ( MEMP) is proposed to solve the element position and to design the excitation. Firstly, an en- hanced matrix is built using the sampling data of the desired planar array radiation pattern and the singular value decomposition(SVD) can be performed. Then the minimun number of elements can be determined. Secondly, the generalized eigen decomposition is employed to calculate the eigenvalues and the estimating signal pa rameters via rotational invariance techniques (ESPRIT) is utilized to pair the eigen- values of each column. Finally, excitations and locations are calculated according tothe correct pairing of eigenvalues. Simulation results are presented to illustrate the efficiency and numerical accuracy of the approach.
出处 《电波科学学报》 EI CSCD 北大核心 2013年第3期540-546,共7页 Chinese Journal of Radio Science
基金 国家自然科学基金资助项目(60736045 U1233103) 中国博士后科学基金(2012M511919)
关键词 平面阵列 稀布阵 增广矩阵束方法(MEMP) 奇异值分解(SVD) 低秩逼近矩阵 plannar array sparse array matrix enhanced and matrix pencil(MEMP) singular value decomposition(SVD) low rank approximation
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参考文献12

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