基于IAA的协方差矩阵重构稳健波束形成方法

Robust beamforming using IAA-based interference-plus-noise covariance matrix reconstruction

摘要:

针对小样本背景下，存在相干信号、相位及阵元位置误差，传统波束形成方法性能不佳的问题，提出了基于迭代自适应法(IAA)的协方差矩阵重构稳健波束形成方法。该方法利用IAA估计出精确的功率谱，并进一步利用IAA估计的功率重构干扰协方差矩阵。重构过程中，将积分区域缩小到三维立体环域，减少无用信息的影响，提高了干扰协方差矩阵的重构精确度。最后通过波束形成抑制干扰信号。由于IAA不依赖于信号的非相干假设，解决了相干信号存在下的方位估计和功率估计。仿真表明，所提出的方法在相干信号、少快拍、相位及阵元位置误差同时存在的情况下，相对于其他波束形成方法，具有最优的信干噪比(SINR)输出，表明该方法具有优良的抑制干扰性能。

Abstract:

In order to address the performance degradation when coherent sources, array perturbations and finite-sampling exist, a robust adaptive beamforming using Iterative Adaptive Approach(IAA)-based interference-plus-noise covariance matrix reconstruction is proposed. Firstly, the method uses the IAA to estimate the accurate power spectrum, and further reconstructs the interference-plus-noise covariance matrix with the power estimated. The method reduces the integral region to the three-dimensional domain to reduce the influence of noise, which improves the reconstruction precision of the interference-plus- noise covariance matrix. Finally, the proposed method suppresses the interference signal by beamforming. Since IAA does not rely on the non-coherent assumptions of the signal, it could estimate the high accuracy of DOA and power when the coherent interference exists. Computer simulations show that, compared with other beamforming methods, the output Signal to Interference plus Noise Ratio(SINR) can achieve the optimal output under coherent interference, array perturbations and finite-sampling situation.