迭代对角加载采样矩阵求逆鲁棒自适应波束形成

Iterative Diagonally Loaded Sample Matrix Inverse Robust Adaptive Beamforming

为有效克服导向矢量大失配误差对自适应波束形成器的影响,该文提出了一种迭代对角加载采样矩阵求逆鲁棒自适应波束形成算法。该算法对传统对角加载算法进行了迭代运算,基于Capon波束形成器的最优权矢量与假定导向矢量的基本关系,将每一步得到的权矢量,对应反解出一个比导向矢量假定值更为准确的导向矢量,并替代假定值,最终逼近真实的期望信号导向矢量。提出的方法在迭代过程中只需一步递推,无需对导向矢量建立不确定集,避免了在每步迭代中运用拉格朗日数值法或凸优化法,且明显提高了波束形成器的输出信干噪比。仿真结果验证了算法的正确性和有效性。

To overcome effectively the influence of large steering vector mismatch on the performance of adaptive beamformer,an Iterative diagonally Loaded Sample Matrix Inverse（ILSMI） robust adaptive beamformer is proposed in this paper.The iterative computation of conventional diagonally Loaded Sample Matrix Inverse（LSMI） method is implemented in the proposed approach.Based on the relationship between the optimal weight vector and the assumed steering vector of the Capon beamformer,the more precise corresponding steering vector of the LSMI optimal weight vector is estimated in each iteration and used to replace the assumed steering vector,and the converged estimation will approach to the real steering vector.The proposed approach can obviously improve the output Signal-to-Interference-and-Noise Ratio（SINR） of the robust beamformer through only one key recursive formula,without any Lagrange multiplier methodology or convex optimization methods in each iteration.The simulation results verify the correctness and validity of the proposed approach.