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Robust adaptive beamforming based on sparse reconstruction using a non-convex optimisation algorithm

机译:基于非凸优化算法的基于稀疏重构的鲁棒自适应波束形成

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摘要

A novel robust adaptive beamforming technique is proposed to solve the problem of performance degradation with one single snapshot. A sparse signal recovery model under the non-convex optimisation framework is first established, which dispenses with the mismatched sample covariance matrix, an indispensable part of most existing beamformers. Then, an iterative algorithm is designed to solve the optimisation problem by using the p-shrinkage operator and the alternating direction method of multipliers. The iteration steps are closed form and convenient to apply in practice. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm.
机译:提出了一种新颖的鲁棒自适应波束成形技术来解决单个快照性能下降的问题。首先建立了在非凸优化框架下的稀疏信号恢复模型,该模型消除了不匹配的样本协方差矩阵,这是大多数现有波束形成器必不可少的部分。然后,设计了一种迭代算法,通过使用p收缩算子和乘数的交替方向方法来解决优化问题。迭代步骤是封闭形式,在实践中很方便应用。仿真结果证明了该算法的有效性和鲁棒性。

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