基于复系数正交权向量分解的宽零陷鲁棒自适应波束形成算法

A Broad Nulling Robust Adaptive Beamforming Algorithm Based on Complex-Coefficient Weight Orthogonal Decomposition

摘要:

针对高动态环境下传统波束形成器零陷失效及现有鲁棒算法在副瓣控制与主瓣性能间的折衷问题,提出了一种基于复系数正交权向量分解的宽零陷鲁棒自适应波束形成算法。该方法依据干噪比动态构建响应掩膜,利用正交投影技术对权向量进行迭代分解与重构,在满足宽零陷约束的同时最大化保留主瓣性能。对20×20平面阵列进行的仿真实验表明,该算法实现了全局低副瓣；在存在干扰漂移和指向误差条件下,相比协方差矩阵锥削等算法,保持了最优的输出信干噪比与光滑且对称的主瓣形状。该技术兼顾了鲁棒性、宽零陷与低副瓣特性,为复杂电磁环境抗干扰提供了有效方案。

Abstract:

To address nulling failure in high-dynamic environments and the trade-off between sidelobe control and mainlobe performance in existing robust beamformers, this paper proposes a robust wide-null adaptive beamforming algorithm based on Complex-coefficient Orthogonal Weight-vector Decomposition. Based on an INR-aware dynamic response mask, the proposed method utilizes orthogonal projection to iteratively decompose and reconstruct the weight vector, satisfying wide-null constraints while maximizing the preservation of mainlobe performance. Simulation results on a planar array demonstrate that the algorithm achieves global low sidelobes. In the presence of interference drift and pointing errors, it maintains the optimal output SINR and a smooth symmetric mainlobe profile compared to conventional algorithms such as Covariance Matrix Tapering. This technology effectively integrates robustness, wide-nulling, and low-sidelobe characteristics, providing a sophisticated anti-interference solution for complex electromagnetic environments.