非线性阵列Khatri-Rao子空间宽带DOA估计

针对非线性阵列，基于Khatri-Rao子空间概念提出一种新的无预估角宽带到达角(direction-of-arrive,DOA)估计方法. 从Khatri-Rao子空间虚拟阵列导向矢量出发，利用虚拟阵列所增加的维数，以流形分离技术构造与到达角无关的宽带聚焦矩阵，无需预估角且估计性能良好. 采用Root-MUSIC算法避免传统算法中的谱峰搜索过程，降低了计算量. 仿真结果表明，该方法与需要预估角的已有Khatri-Rao子空间宽带DOA估计方法FKR-RSS相比，具有相近的估计精度和目标分辨力. 在信号源数大于阵元数的情况下，其性能优于FKR-RSS.

Khatri-Rao Subspace Wideband DOA Estimation for Nonlinear Array

A Khatri-Rao subspace based wideband direction-of-arrive (DOA) estimation algorithm for nonlinear arrays without preliminary angle estimation is proposed. From steering vectors of the Khatri-Rao subspace virtual array, the wideband focusing matrix regardless of DOAs is constructed with a manifold separation technique.Benefited from the increased dimensions of the Khatri-Rao subspace virtual array, preliminary angle estimation can be avoided and the algorithm still performs well. On the other hand, by using Root-MUSIC, this method can avoid expensive spectrum searching used in conventional methods so as to reduce the computational burden. Simulations show that performance of the proposed method is close to the preliminary angle estimation needed Khatri-Rao subspace wideband DOA estimation algorithm, FKR-RSS. The proposed method performs better than FKR-RSS when the number of sources is more than the number of sensors.