一种基于支持向量机的对角加载鲁棒波束形成方法

为了有效克服波达方向矢量失配,以及存在阵元扰动而导致的阵列流形向量失配对自适应波束形成器的影响,提出了一种基于支持向量机的对角加载鲁棒波束形成方法。该方法在分析线性约束最小方差波束形成器的基础上,研究了传统的对角加载算法对波束形成器鲁棒性的改善,将基于结构风险最小化原理的支持向量机算法应用于鲁棒波束形成。数值仿真实验表明:在无失配的理想情况和有失配的实际情况下,基于支持向量机的波束形成算法均可以提高波束形成的鲁棒性。

The Robust Diagonal Loading Beamforming Method Using Support Vector Machines

A robust diagonal loading (DL) beamforming method is proposed, which can effectively over- come the influence of DOA(direction of arrival) mismatch and sensor position uncertainties on the per- formance of adaptive beamformer. The proposed method exhibits the enhanced robustness of the beam- formers with the traditional method of DL based on analysis of linear constrained minimum variance beam- former. Then the support vector machine (SVM) algorithm is applied to the robust beamforming, which is based on the principle of structural risk minimization. The simulation results show that the SVM-based beamforming method enhances the robustness in terms of desired signal array manifold vector errors in an ideal scenario of no-mismatch and an actual scenario of mismatch, respectively.