混响编码孔径深亚波长定位
Deeply Sub-Wavelength Localization with Reverberation-Coded-Aperture
摘要：
从远场获得关于场景的亚波长信息而无需侵入性近场操纵是波动工程中的基本挑战。然而，众所周知，波在复杂介质中的停留时间决定了波对扰动的敏感度。现代编码孔径成像器利用由复杂介质提供的自由度（DoF）作为自然复用器，但是不识别和获得将感兴趣对象放置在复杂介质外部或内部之间的根本差异。在这里，我们表明，定位亚波长对象的精度可以提高几个数量级，只需将其封闭在其远场与混响混沌腔。我们将深度学习确定为合适的噪声鲁棒性工具，以提取在多路复用测量中编码的亚波长信息，实现远远超出训练数据中可用的分辨率。我们证明了我们的发现在微波域：利用一个简单的可编程元表面的配置自由度，我们本地化一个亚波长的对象内的混沌腔的分辨率为$λ/76$使用强度只有单频单像素测量。我们的研究结果可能在光声成像以及基于反射弹性波、声音或微波的人机交互中具有重要的应用。
英文摘要：
Accessing sub-wavelength information about a scene from the far-field without invasive near-field manipulations is a fundamental challenge in wave engineering. Yet it is well understood that the dwell time of waves in complex media sets the scale for the waves' sensitivity to perturbations. Modern coded-aperture imagers leverage the degrees of freedom (DoF) offered by complex media as natural multiplexor but do not recognize and reap the fundamental difference between placing the object of interest outside or within the complex medium. Here, we show that the precision of localizing a sub-wavelength object can be improved by several orders of magnitude simply by enclosing it in its far field with a reverberant chaotic cavity. We identify deep learning as suitable noise-robust tool to extract sub-wavelength information encoded in multiplexed measurements, achieving resolutions well beyond those available in the training data. We demonstrate our finding in the microwave domain: harnessing the configurational DoF of a simple programmable metasurface, we localize a sub-wavelength object inside a chaotic cavity with a resolution of $λ/76$ using intensity-only single-frequency single-pixel measurements. Our results may have important applications in photoacoustic imaging as well as human-machine interaction based on reverberating elastic waves, sound or microwaves.
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