MIMO阵列中基于PM和降维变换的高效DOA估计算法

在这篇论文中，我们讨论MIMO阵列中的高效DOA估计方法。由于PM算法不需要对互相关矩阵进行特征值分解，也不需要对接收的数据进行奇异值分解，因此它的计算量可以显著的变小。因此MIMO阵列中基于PM算法和降维变换的DOA估计方法被提出了，而且这种提出的算法比PM算法有更低的计算复杂度。这种算法在没有频谱搜索的情况下效果很好。此外，它比PM算法的角度估计性能稍好。DOA估计中的估计误差的方差和克拉美罗界也可以导出。仿真结果验证了提出的算法的有效性。

Computationally Efficient DOA Estimation for MIMO Array using Propagator Method and the Reduced-Dimension Transformation

In this paper, we consider computationally efficient direction of arrival (DOA) estimation for monistatic multiple-input multiple-output (MIMO) array. The computational loads of the propagator method (PM) can be significantly smaller since the PM does not require any eigen-value decomposition of the cross correlation matrix and singular value decomposition of the received data. DOA estimation for the MIMO array using PM and reduced-dimension transformation is proposed, and the proposed algorithm has less computational complexity than PM. The proposed algorithm works well without spectrum searching. Furthermore, the proposed algorithm still has slightly angle estimation performance than PM. The variance of the estimation error and Cramér-Rao Bound (CRB) of DOA estimation are derived. Simulation results verify the usefulness of the proposed algorithm.