一种基于协方差矩阵重构的鲁棒波束形成方法

A robust beamforming algorithm based on covariance matrix reconstruction

针对鲁棒Capon波束形成算法中采用牛顿迭代求解对角加载因子时,运算量大且算法旁瓣增益高的问题,提出了一种改进的稳健波束形成算法。首先对干扰协方差矩阵进行重构,然后将重构的协方差矩阵投影到噪声子空间,使期望信号导向矢量在噪声子空间投影最优,最后精确求解对角加载因子。该方法的运算量低于RCB算法中牛顿迭代和最差性能最优(WCPO)算法中凸规划运算,并且提高了加载因子的计算精度。实际仿真结果表明,改进算法有效克服了信号方向估计误差,具有更低且稳定的旁瓣增益,输出信干噪比性能优于现有其他方法。

In view of the robust Capon beamforming algorithm, the Newton iterative method is utilized to obtain the diagonal loading factor, which leads to problems of large amount of computation and high side lobe gain. This paper propose new robust beamforming algorithm. Firstly, the interference covariance matrix is reconstructed, and then the reconstructed covariance matrix is projected to the noise subspace, so that the optimum projection of the desired signal steering vector in the noise subspace can be achieved, and the diagonal loading factor is accurately solved. The computation of the proposed algorithm is less than RCB and WCPO method, which improve calculation accuracy of the load factor. Practical simulation results show that the proposed method overcomes the problem of signal direction estimation errors effectively, has a lower beam side-lobe gain than RCB and WCPO algorithm, and outcomes other existing methods.