[Paper Review] Large-aperture computational single-sensor microwave imager using 1-bit programmable coding metasurface at single frequency

Dapeng Lao, Lianlin Li+3 more|arXiv (Cornell University)|May 11, 2017

Metamaterials and Metasurfaces Applications25 references3 citations

TL;DR

This paper proposes a large-aperture, single-sensor microwave imager using a 1-bit programmable coding metasurface at a single frequency, leveraging column-row-wise coding to reduce data acquisition time and improve temporal and spatial resolution. It enables high-resolution imaging by solving a sparsity-regularized convex optimization problem, achieving theoretical recovery guarantees comparable to conventional pixel-wise coded systems, validated by simulations and experiments.

ABSTRACT

The microwave imaging based on inverse scattering strategy holds important promising in the science, engineering, and military applications. Here we present a compressed-sensing (CS) inspired large- aperture computational single-sensor imager using 1-bit programmable coding metasurface for efficient microwave imaging, which is an instance of the coded aperture imaging system. However, unlike a conventional coded aperture imager where elements on random mask are manipulated in the pixel-wised manner, the controllable elements in the proposed scheme are encoded in a column-row-wised manner. As a consequence, this single-sensor imager has a reduced data-acquisition time with improved obtainable temporal and spatial resolutions. Besides, we demonstrate that the proposed computational single-shot imager has a theoretical guarantee on the successful recovery of a sparse or compressible object from its reduced measurements by solving a sparsity-regularized convex optimization problem, which is comparable to that by the conventional pixel-wise coded imaging system. The excellent performance of the proposed imager is validated by both numerical simulations and experiments for the high-resolution microwave imaging.

Motivation & Objective

• To develop a computationally efficient, large-aperture microwave imaging system using a single sensor.
• To reduce data acquisition time and enhance temporal and spatial resolution compared to conventional coded aperture imaging.
• To enable high-resolution imaging of sparse or compressible objects using reduced measurements.
• To provide theoretical recovery guarantees for object reconstruction via compressed sensing.
• To validate the system's performance through numerical simulations and experimental results.

Proposed method

• The system employs a 1-bit programmable coding metasurface where elements are encoded in a column-row-wise pattern rather than pixel-wise.
• The coding pattern modulates the incident microwave wavefront, generating a multiplexed measurement signal.
• A compressed-sensing (CS)-inspired framework is used to reconstruct the object from reduced measurements.
• The reconstruction problem is formulated as a sparsity-regularized convex optimization problem to ensure stable and accurate recovery.
• The system operates at a single frequency, enabling efficient and focused imaging.
• Theoretical analysis confirms that the measurement matrix satisfies restricted isometry property (RIP) under certain conditions, guaranteeing successful recovery.

Experimental results

Research questions

• RQ1 Can a single-sensor microwave imaging system achieve high resolution with reduced data acquisition time?
• RQ2 How does column-row-wise coding compare to pixel-wise coding in terms of imaging efficiency and resolution?
• RQ3 What is the theoretical recovery guarantee for reconstructing sparse objects using this system?
• RQ4 Can the proposed system achieve performance comparable to conventional pixel-wise coded imaging with fewer measurements?
• RQ5 How does the system perform under real-world experimental conditions?

Key findings

• The proposed imager achieves high-resolution microwave imaging with significantly reduced data acquisition time due to column-row-wise coding.
• The system demonstrates improved temporal and spatial resolution compared to conventional single-sensor coded aperture imagers.
• Theoretical analysis confirms that the measurement matrix satisfies the restricted isometry property (RIP), ensuring stable and robust object recovery.
• Numerical simulations and experiments validate the system's ability to reconstruct sparse or compressible objects accurately from reduced measurements.
• The performance of the proposed system is comparable to that of conventional pixel-wise coded imaging systems in terms of reconstruction quality.
• The system operates effectively at a single frequency, enabling focused and efficient imaging with a large-aperture configuration.