一种具有双重鲁棒性的自适应波束形成算法

提出了一种具有双重鲁棒性的自适应波束形成算法，以克服有限采样效应和方向矢量误差引起的波束性能下降。该算法使用对角加载提高鲁棒性，并通过协方差矩阵拟合和优化最坏情况下的波束性能确定对角加载因子。在此基础上，本文得出了最优加载因子的近似表达式，揭示了哪些因素可以影响最优加载因子，以及如何影响。和该领域现有的其他算法相比，本算法运算量更低，具有更好的鲁棒性。计算机仿真对该算法进行了验证。

A Novel Approach of Doubly Robust Adaptive Beam Formation

In this paper, a novel approach of doubly robust adaptive beam formation (RABF) is proposed in order to improve the robustness against finite-sample effects and steering vector errors. This goal is achieved by diagonal loading and selecting loading level based on covariance fitting and worst-case performance optimization. Moreover, a simple closed-form solution to the optimal loading, which reveals how different factors affect the optimal loading, is derived here after some approximations. Compared with many related methods, the proposed one consumes less computational task and achieves robustness against not only steering vector errors, but also finite-sample effects. Its excellent performance is demonstrated via a number of numerical examples.