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Concurrent adaptive beamforming for standard hexagonal array based on dual norm-constraint correntropy in the presence of alpha stable noise

机译:在α稳定噪声存在下,基于双重范数约束性的标准六角形阵列的并行自适应波束成形

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This article presents dual norm-constraint correntropy beamforming methods for standard hexagonal array (SHA) to mitigate the effects of alpha stable noise and maintain the sparsity of filter coefficients. Both goals are achieved simultaneously through the use of norm regularization constraint and the novel convex combination technique. Firstly, we construct constrained optimization equations considered the constraints present in the constrained least-mean-square (CLMS) algorithm by incorporating the maximum correntropy criterion (MCC). In addition, in order to decrease the number of active elements for limited power supply array system, we introduce an L1-norm equation to the list of constraints of the adaptive filter that forces the coefficients with small magnitudes to zero. Then, we utilize the convexity and stability of L2-norm to devise the constrained maximum correntropy gradient L2-norm (CMCG-L2) for further reducing the misadjustment caused by alpha noise and improving the directivity performance of the adaptive beamformer. A novel convex combination scheme is also reported to satisfy the conflicting requirements between the sparsity and mean-square-error. Our simulation results demonstrate the superiority of the proposed methods over other previously developed beamforming techniques.
机译:本文介绍了用于标准六边形阵列(SHA)的双重范数约束性熵波束成形方法,以减轻alpha稳定噪声的影响并保持滤波器系数的稀疏性。通过使用范式正则约束和新颖的凸组合技术,可以同时实现两个目标。首先,我们通过结合最大熵准则(MCC),构造了考虑约束最小均方(CLMS)算法中存在约束的约束优化方程。另外,为了减少有限电源阵列系统的有源元件数量,我们在自适应滤波器的约束列表中引入了L1-范数方程,该方程将小幅度系数强制为零。然后,我们利用L2-范数的凸性和稳定性来设计受约束的最大熵梯度L2-范数(CMCG-L2),以进一步减少由α噪声引起的失调,并改善自适应波束形成器的指向性。还报道了一种新颖的凸组合方案,以满足稀疏度和均方误差之间的冲突要求。我们的仿真结果证明了所提出的方法优于其他先前开发的波束成形技术。

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