多级嵌套L型阵列及其测向算法

针对基于偶数(2q)阶累积量的测向算法中测向性能提高有限的问题，提出了一种基于多级嵌套 L 型阵列的2维测向算法。首先利用阵列的多级嵌套结构和2q阶累积量，形成具有更多自由度的虚拟均匀面阵；然后使用2维平滑方法，恢复其2q阶累积量矩阵的秩； 采用2维MUSIC算法，进行方位角和俯仰角的估计。与常规的2q MUSIC 算法相比，所提算法不仅具有更好的测向精度，而且由于虚拟均匀阵包含更多的虚拟阵元，因此能够估计更多信源的方位角。另外，针对该L型阵列的最优配置问题，推导了各级子阵阵元数的最优和次优分配表达式。仿真结果表明这些结论的正确性。

Multiple Level Nested L-Shaped Array and Its Direction-Finding Algorithm

To avoid the problem that the performance improvement of direction of arrival (DOA) estimation algorithms based on arbitrary even order  (2q) cumulants is limited, an azimuth elevation direction finding algorithm based on multiple level nested L shaped array is present. The multiple level nested structure and  2q th order cumulants are used to form a virtual uniform rectangular array with more degrees of freedom. Then, a novel algorithm based on the idea of 2D spatial smoothing is exploited to recover the rank of the  2q th order cumulant matrix. Azimuth and elevation angles are estimated by utilizing two dimensional multiple signal clasification (2D MUSIC) algorithm. Compared with the classical  2q MUSIC, the proposed algorithm can provide the higher DOA performance, and be able to estimate the angles of more sources due to the virtual uniform array containing more virtual array elements. In addition, the optimal and suboptimal allocation expression of all levels sub arrays is derived to obtain the optimal L shaped array. Simulation results verify the correctness of these conclusions.