Compressive equivalent source method based on particle velocity measurements for near-field acoustic holography

Wen-Qian Jing, Guang-Sheng Liu
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Abstract

In order to solve the problems of spatial resolution limit and reduce the measurement cost, the compressive sensing theory and the sparse regularization are applied to the near-field acoustic holography (NAH) technology. In the previous works, the Equivalent Source Method (ESM)-based NAH has been extended in the sparsity framework by sampling the sound pressure signals sparsely. However, this Compressive ESM (CESM) mode would suffer from the low precision problem in the particle velocity reconstruction. To improve the reconstruction accuracy of the particle velocity, this paper is going to take the sparse particle velocity as the input of NAH to establish a new CESM mode based on the particle velocity measurement. In the meantime, the number of sampling points will be reduced greatly without losing the reconstruction accuracy when compared to the conventional ESM with the Tikhonov regularization based on the particle velocity measurement. Several numerical simulation experiments have been carried out to examine the performance of the proposed model. The results show that the proposed model delivers a satisfactory performance in the reconstruction of both the pressure and particle velocity on the condition that the number of sampling points is much smaller than that of the conventional ESM, and the proposed model performs much better than the existing CESM mode based on the sound pressure measurement especially when reconstructing the particle velocity.
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基于粒子速度测量的近场声全息压缩等效源方法
为了解决空间分辨率限制和降低测量成本的问题,将压缩感知理论和稀疏正则化技术应用于近场声全息技术。在以往的工作中,基于等效源方法(ESM)的声压信号稀疏采样在稀疏框架中得到了扩展。但是,压缩ESM (CESM)模式在粒子速度重建中存在精度低的问题。为了提高粒子速度的重建精度,本文将稀疏粒子速度作为NAH的输入,建立一种基于粒子速度测量的新的CESM模式。同时,与传统的基于粒子速度测量的Tikhonov正则化ESM相比,在保证重构精度的前提下,大大减少了采样点的数量。为了验证所提出模型的性能,进行了一些数值模拟实验。结果表明,该模型在采样点数量远少于传统ESM的情况下,对声压和粒子速度的重构都有较好的效果,且在重构粒子速度方面明显优于现有的基于声压测量的CESM模型。
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