基于稀疏互质电磁矢量阵列的MUSIC算法

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。

MUSIC Algorithm Based on Sparse Coprime Electromagnetic Vector Arrays

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.