互质线阵中一种基于共轭增广的DOA估计算法

论文开展互质线阵下的空间谱估计研究。通过利用信号二阶统计量的共轭增广特性，提出互质阵下基于共轭增广的酉旋转不变性进行信号参数估计 (Conjugate augmented unitary estimation of signal parameters via rotational invariance technique, CA-UESPRIT)波达方向(Direction of arrival, DOA)估计算法。该算法先利用不同时长间隔下接收信号的二阶统计量，构造共轭增广虚拟阵列以扩展阵列孔径和提高空间自由度。然后采用基于互质特性的联合UESPRIT算法实现DOA估计。相比于传统互质线阵下的联合UESPRIT算法，CA-UESPRIT算法DOA估计性能更优。此外，通过酉变换可以将ESPRIT算法的协方差矩阵从复数域转化到实数域，降低了复杂度的同时保证了测向精度。仿真结果证实了所提算法的有效性。

DOA Estimation Algorithm Based on Conjugate Augmentation for Coprime Linear Array

The paper implements the research of spatial spectrum estimation for coprime linear array. By utilizing the conjugate augmented characteristic of the second-order statistic of the signals, a conjugate augmented unitary estimation of signal parameters via rotational (ESPRIT) (CA-UESPRIT) direction of arrival (DOA) estimation algorithm is proposed. By using the second-order statistics of the received signals with different time lags, the algorithm firstly constructs a conjugate augmented virtual array to expand the array aperture and improve degrees of freedom (DOFs), subsequently, achieves the DOA estimation by exploiting the coprime property based joint UESPRIT algorithm. Compared to the traditional joint UESPRIT algorithm for coprime linear array, better DOA estimation performance can be achieved by CA-UESPRIT algorithm. In addition, the covariance matrix of the ESPRIT algorithm can be transformed from the complex domain to the real domain by the unitary transform, which reduces the complexity but ensures the estimation accuracy. The simulation results verify the effectiveness of the proposed algorithm.