Presentation
14 May 2018 Optimizing the information content of metasurface apertures for computational millimeter-wave imaging (Conference Presentation)
David R. Smith
Author Affiliations +
Abstract
We analyze the information content of metasurface apertures in the context of a millimeter-wave computational imaging system. Each of the apertures consists of a waveguide- or cavity-backed metasurface layer, which produces a series of quasi-random field patterns as a function of the excitation frequency. The metasurface layer is a conducting surface patterned with subwavelength, metamaterial slots, each of which couples energy from the guided wave to the scene. A single measurement of a scene consists of illuminating the scene with a transmit aperture and detecting the back-scattered field at a receive aperture. Repeating this process over all combinations of transmit and receive apertures and over all frequencies produces a set of measurements that can be used to estimate the scene reflectivity using computational imaging methods. While the maximum number of independent measurement modes for a composite aperture is set by bandwidth and diffraction limits, the actual number of modes available from an aperture can be substantially smaller due to spatial correlation of the field patterns from one mode to another. To minimize this correlation, a variety of design steps can be taken, including optimizing the quality-factor of an aperture and optimizing the Fourier space coverage as determined by the specific number and arrangement of metasurface elements. These design considerations are quite general, and apply to a wide range of metasurface designs. We present several metasurface designs and show how their specific architecture relates to the overall imaging performance of the system.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David R. Smith "Optimizing the information content of metasurface apertures for computational millimeter-wave imaging (Conference Presentation)", Proc. SPIE 10656, Image Sensing Technologies: Materials, Devices, Systems, and Applications V, 106561D (14 May 2018); https://doi.org/10.1117/12.2305842
Advertisement
Advertisement
KEYWORDS
Millimeter wave imaging

Imaging systems

Computational imaging

Waveguides

Composites

Computing systems

Diffraction

Back to Top