基于互协方差的L型嵌套阵列二维波达方向估计

为了解决L型均匀阵列波达方向（DOA）估计分辨率较低、估计信源数受限于阵元数、估计精度易受信噪比影响等问题，提出一种基于互协方差的L型嵌套阵列二维DOA估计算法。利用不同子阵间互协方差矩阵产生较长无冗余阵元的虚拟阵列，消除噪声干扰；利用虚拟阵列及其共轭矩阵构建等效协方差矩阵，实现虚拟阵列信号的解相干；采用旋转不变子空间技术对等效协方差矩阵进行处理，得到目标的角度信息；基于虚拟阵列等效信源的唯一性进行空间信源的角度匹配。对所提算法的DOA估计有效性进行仿真验证，结果表明，在阵元数相同情况下，该算法与L型均匀阵列相比在低信噪比环境下拥有更高的估计精度，能够辨识更多的空间信源。

Two-dimensional Direction-of-arrival Estimation for L-shaped Nested Array Based on Cross-covariance Matrix

The direction of arrival （DOA）estimation for L-shaped uniform antenna array is limited by low resolution, number of incident signals and signal-to-noise ratio. A two-dimensional DOA estimation algorithm for L-shaped nested array based on cross-covariance matrix is proposed to solve this problem. In the proposed algorithm, the cross-covariance matrixes of different sub-arrays are used to generate longer virtual arrays without redundant elements, which eliminate the noise. To cope with the coherent signals of virtual arrays, several equivalent covariance matrixes are constructed by using the signal of virtual arrays and its conjugate signal. The rotational invariance technique is used to deal with the equivalent covariance matrixes to obtain the angle of incident signals, and the angles are matched by using the uniqueness of equivalent signal vectors of virtual arrays. The effectiveness of the proposed algorithm for DOA estimation was verified. The simulated results show that the proposed algorithm can achieve better DOA estimation performance in low SNR environment and identify more spatial sources compared to the L-shaped uniform array with the same number of array elements.