| 利用完全复数极限学习机增强近场声全息空间分辨率 |
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| 引用本文： | 周鹤峰,曾新吾.利用完全复数极限学习机增强近场声全息空间分辨率[J].声学学报,2019,44(3):273-284. |
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| 作者姓名： | 周鹤峰 曾新吾 |
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| 作者单位： | 国防科技大学气象海洋学院 长沙 410073 |
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| 基金项目： | 国防科技大学科研计划重点项目(JC15-11-01)资助 |
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| 摘 要： | 针对稀疏测量阵列条件下近场声全息重建结果空间分辨率不足的问题,提出了一种基于完全复数极限学习机的全息声压插值方法。该方法首先将已测量的全息面复声压和对应的测点坐标组成训练样本输入完全复数极限学习机,接着把插值点的坐标代入训练好的极限学习机,得到相应位置的复声压,实现全息数据的插值。利用插值后的全息数据进行重建,并与不做插值处理的重建结果和传统插值处理后的重建结果比较。仿真和实验结果均表明:与不做插值相比,该方法在不增加传声器的条件下显著提高了重建结果的空间分辨率。与基于支持向量机或传统极限学习机的插值方法相比,该方法速度更快,插值后重建结果精度更高。同时,通过添加噪声干扰验证了该方法的稳健性。
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| 关 键 词： | 近场声全息 空间分辨率 完全复数极限学习机 声压插值 |
| 收稿时间： | 2017-11-29 |
Spatial resolution enhancement of nearfield acoustic holography using the fully complex extreme learning machine |
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| Affiliation: | College of Meteorology and Oceanology, National University of Defense Technology Changsha 410073 |
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| Abstract: | For the problem of insufficient spatial resolution of nearfield acoustic holography reconstruction under the sparse measurement array condition, a hologram pressure interpolation method based on the fully complex extreme learning machine is proposed. Firstly, the measured complex hologram pressures and the planar coordinates of the corresponding measurement points are combined into the training samples. They are used to train the fully complex extreme learning machine. Then, the planar coordinates of the interpolation points are introduced into the trained machine to generate the corresponding pressures, achieving the interpolation of hologram data. Finally, the interpolated hologram pressures are used to reconstruct. The results are compared with those without the interpolation and with the traditional interpolation. Numerical simulations and experimental results show that compared to the results without the interpolation, the proposed method significantly improves the spatial resolution of the reconstructed results without increasing the microphones. Compared to the interpolation method based on the support vector machine or the traditional extreme learning machine, the proposed method is faster and its reconstructed result is more accurate. The robustness of this method is also verified by adding noise interference. |
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