Deeply Sub-Wavelength Localization with Reverberation-Coded-Aperture

TL;DR

This paper demonstrates that enclosing a sub-wavelength object in a reverberant chaotic cavity significantly enhances localization precision, leveraging deep learning to extract super-resolution information from multiplexed wave measurements in the microwave domain.

Contribution

It introduces a novel approach of using reverberant cavities and deep learning to achieve super-resolution localization of sub-wavelength objects from far-field measurements.

Findings

Achieved localization resolution of λ/76 in microwave experiments.

Deep learning effectively extracts sub-wavelength information from noisy, multiplexed data.

Reverberant cavities enhance the sensitivity of wave-based sensing methods.

Abstract

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 $\lambda/76$ 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.