ROI-Steerable High-SNR Computational Imaging via Transmissive Coding Metasurface

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Abstract
Computational microwave imaging (CMI) based on metasurface apertures effectively simplifies the system hardware. However, conventional random-field approaches suffer from low energy efficiency, leading to a poor signal-to-noise ratio (SNR) that severely degrades imaging quality. To address this, this letter proposes a bunching imaging method featuring a steerable region of interest (ROI) utilizing a 1-bit transmissive coding metasurface and experimentally validates its performance. By partitioning the aperture into subarrays and programming each to focus on a random point within the ROI, the proposed strategy addresses the trade-off between energy concentration and pattern diversity. Experimental results demonstrate that this transmissive implementation increases the peak power of the radiated field by approximately 13 dB over the conventional method while maintaining low mutual coherence. This enhancement leads to improved imaging quality under real experimental conditions, validating the proposed system as an effective solution for high-SNR computational imaging.

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