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基于稀疏互质电磁矢量阵列的MUSIC算法

MUSIC Algorithm Based on Sparse Coprime Electromagnetic Vector Arrays

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【作者】 邵华苏卫民顾红王灿

【Author】 Shao Hua Su Wei-min Gu Hong Wang Can(School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology,Nanjing 210094,China)

【机构】 南京理工大学电子工程与光电技术学院

【摘要】 为增加传统MUSIC算法可分辨的信号源数,该文构造了一对具有互质关系的2维稀疏电磁矢量阵列,并基于此阵列提出了一种基于3维平滑的MUSIC算法。该算法利用两个阵列间的互质关系形成具有更多自由度的互质差合成阵列,并基于3维(2维空域加极化域)平滑算法恢复其自相关矩阵的秩,达到应用于传统MUSIC算法的目的。该算法的最大优势是仅使用二阶统计量即可系统地增加了原阵列的自由度。计算机仿真结果表明所提算法能估计多于物理阵元数的信号且分辨率高。

【Abstract】 To increase signal number distinguished by traditional MUSIC algorithm,this paper proposes a MUSIC algorithm based on three-dimensional smoothing by a coprime pair of two-dimensional sparse electromagnetic vector arrays.The coprime relationship between two arrays is used in the algorithm to generate a coprime co-array with more degrees of freedom.And the rank of its autocorrelation matrix is restored by three-dimensional(two-dimensional spatial domain and polarization domain) smoothing algorithm in order to apply to the traditional MUSIC algorithm.A major advantage of this method is that the freedom of the original array is also systematically increased by even using second-order statistics.Computer simulation results show that the proposed algorithm can estimate the number of signals more than the number of physical array elements and have high resolution.

【基金】 南京理工大学自主科研专项计划(2010ZDJH05);国家部委基金;高等学校博士学科点专项科研基金(20113219110018)资助课题
  • 【文献出处】 电子与信息学报 ,Journal of Electronics & Information Technology , 编辑部邮箱 ,2012年09期
  • 【分类号】TN911.7
  • 【被引频次】15
  • 【下载频次】312
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