一种简化的鲁棒波束形成算法

在阵列导向矢量不存在误差的条件下,传统的最小方差波束形成器(MVB)具有良好的分辨精度和抗干扰能力.然而,MVB算法的主要问题在于不具有鲁棒性,不能克服未知导向矢量误差的影响.因此对角加载以及相应的扩展算法已经成为一种提高MVB算法鲁棒性的常用方法.该文对基于椭球形导向矢量不确定集的鲁棒MVB算法进行了简化,该简化算法是在对导向矢量附加一个球形不确定集约束的条件下推导出来的,具有较低的计算复杂度和更高的数字稳定性.仿真结果表明,在导向矢量误差存在的情况下该算法是有效的.

A simplified robust beamforming algorithm

The conventional minimum variance beamformer (MVB) is known to have better resolution and much better anti-interference capability when the array steering vector is accurately known. However, the major problem of the MVB is that it lacks robustness when there are unknown array steering vector errors. Therefore, diagonal loading and its extended versions have been a popular approach to improve the robustness of the MVB algorithm. In this paper, the authors simplify the robust MVB algorithm based on an ellipsoidal uncertainty set. The simplified algorithm has been derived by enforcing a spherical uncertainty set constraint on the array steering vector. The new algorithm has lower computation complexity and higher numerical stability. Simulation results show that the new algorithm is effective in the presence of steering vector errors.