宽带波束形成的稀疏传声器阵列设计

M. Hawes, W. Liu
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引用次数: 15

摘要

稀疏宽带传感器/传声器阵列设计问题是高度非线性的,传统上采用遗传算法、模拟退火或其他类似的优化方法来解决。这是一个非常耗时的过程,并不能保证最佳解决方案。本文从压缩感知的角度对该问题进行了研究,并提出了一种基于压缩感知的方法。虽然已经提出了基于cs的窄带阵列设计方法,但将其扩展到宽带情况并不简单,因为每个传感器/麦克风都有多个相关系数,简单地最小化权重系数的l1范数以获得稀疏阵列解是不够的。为此,推导了一种改进的l1范数最小化方法,并通过设计实例验证了其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sparse microphone array design for wideband beamforming
The sparse wideband sensor/microphone array design problem is highly nonlinear and it is traditionally solved by genetic algorithms, simulated annealing or other similar optimization methods. This is an extremely time-consuming process and an optimum solution is not guaranteed. In this work, this problem is studied from the viewpoint of compressive sensing (CS) and a CS-based method is provided. Although there have been CS-based methods proposed for the design of narrowband arrays, its extension to the wideband case is not straightforward, as there are multiple coefficients associated with each sensor/microphone and it is not sufficient to simply minimize the l1 norm of the weight coefficients to obtain a sparse array solution. To achieve this, a modified l1 norm minimization method is derived and its effectiveness is verified by design examples.
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