Super-resolution imaging of low-frequency sound sources using a corrected monopole time reversal method

Super-resolution imaging of low-frequency sound sources using a corrected monopole time reversal method
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使用校正单极子时间反转方法对低频声源进行超分辨率成像

DOI:
10.1016/j.jsv.2017.08.039
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发表时间:
2017-12
影响因子:
4.7
通讯作者:
Liang Xu
Liang Xu
中科院分区:
工程技术2区
文献类型:
--
作者:
Chuan-Xing Bi;Yong-Chang Li;Yong-Bin Zhang;Liang Xu

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仅记录和重传声场的时间反转(MTR)方法的局限性在于焦点的空间分辨率不能优于半个波长,因此它不适合于定位低频声源。本文首先将MTR方法得到的时间反演压力场变换到波数域,然后将其分解为控制聚焦空间分辨率的滤波器项和与声源和聚焦面有关的声源项。随后,通过用偶极TR(DTR)方法的时间反演压力梯度场滤波器、常数滤波器和经验滤波器代替MTR方法的时间反演压力场滤波器,对MTR方法的时间反演压力场进行了校正,从而可以包括更多的倏逝波并获得亚波长聚焦。数值模拟和实验结果表明,与原MTR方法相比,修正后的MTR方法能够显著提高低频聚焦的空间分辨率。研究还发现,当信噪比较高(一般在30 dB以上)时,常数滤波器适用; DTR方法的时反压力梯度场滤波器即使在低信噪比情况下也能稳定工作;当信噪比高于10 dB时,经验滤波器的性能最佳。
A limitation of the monopole time reversal (MTR) method, which records and retransmits the monopole field only, is that the spatial resolution of the focus cannot be better than half a wavelength, and therefore it is not suitable for locating low-frequency sound sources. In this paper, the time-reversed pressure field obtained by the MTR method is first transformed into the wavenumber domain, and is then decomposed into a filter term that controls the spatial resolution of the focus and a source term that is related to the sound source and focusing plane. Subsequently, a correction is made to the time-reversed pressure field of the MTR method by replacing its filter with the filter for the time-reversed pressure gradient field of the dipole TR (DTR) method, a constant filter and an empirical filter, which makes it possible to include many more evanescent waves and obtain subwavelength focusing. Numerical simulation and experimental results show that compared to the original MTR method, the corrected one is able to dramatically improve the spatial resolution of the focus at low frequencies. It is also found that the constant filter is applicable when the signal-to-noise ratio (SNR) is high (generally above 30 dB), the filter for the time-reversed pressure gradient field of the DTR method works stably even in the situation of low SNR, and the empirical filter performs best when the SNR is above 10 dB.
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