Metagrating-based Single-pixel Acoustic Direction Finding
Thomas Macleod, Sebastian Oberst, David A. Powell, Yan Kei Chiang
TL;DR
This work addresses acoustic direction finding with reduced hardware by introducing a metagrating-based single-pixel framework. A two-layer metagrating encodes incident fields into distinct diffraction-order patterns, enabling a compressive sensing formulation where a single sensor suffices to recover 360° directions. Numerical simulations and experimental validation show robust 360° localisation across frequencies and under noise, with a modest bandwidth requirement (e.g., 5.2 kHz) and reconstruction strengths remaining high. The approach offers a compact, low-cost, scalable alternative to traditional microphone arrays, with potential applications in industrial monitoring, target tracking, and non-destructive health sensing.
Abstract
Acoustic metamaterials provide new opportunities for compact and efficient wavefront manipulation, extending beyond conventional bulky and power-intensive phased-arrays. In this work, we exploit the spatial encoding properties of the acoustic metagrating aperture to transform incident acoustic fields into compressed measurements for single-pixel acoustic source localisation. The proposed method enables accurate direction finding of acoustic sources over both 180 and 360 degrees angular ranges. Numerical simulations confirm the robustness of the metagrating-based compressive sensing approach against noise and limited sampling. Experimental validation is conducted to verify its feasibility with practical metagrating prototyes. Compared wiith tranditional array-based localisation techniques, the single-pixel metagrating system significantly reduces hardward complexity while maintaining high localisation accuracy. These findings demonstrate the potential of integrating compressive sensing with acoustic metagratings for compact, low-cost, scalable source detection systems, with prospective applications in industrial monitoring, target tracking and non-destructive health monitoring.
