基于相关域的二维自适应波束形成算法

Two-dimensional Adaptive Beamforming Based on Correlation Matrix

该文针对使用最小方差无失真响应算法进行2维波束形成时需要大量采样数据和庞大计算复杂度这一问题,提出一种基于相关域的2维自适应波束形成算法。通过将高维权向量分解成两个低维权向量的Kronecker积形式,使用双迭代算法利用相关域信息求解出两个低维权向量,从而降低了估计采样相关矩阵所需的采样数据和计算量。实验仿真表明,所提算法具有良好的收敛性能,在采样数较小的情况下,能够更好地抑制干扰信号。

Considering the issue that two-dimensional beamforming usually takes a great deal of sampling data and has very high computation complexity by using Minimum Variance Distortionless Response （MVDR） beamformer, a Two-Dimensional Adaptive Beamforming （TDAB） algorithm based on correlation matrix is proposed. High-dimensional weight vector is written as the Kronecker product of two low-dimensional weight vectors. By utilizing a bi-iterative algorithm, two low-dimensional weight vectors can be solved on the basis of correlation matrix, which decrease the computational complexity and the number of training samples for correlation matrix estimates.Simulations results demonstrate that TDAB can converge very well and achieve better performance of interference suppression in the presence of short data records.