Optimization of a Sparse Aperture Configuration for Millimeter-Wave Computational Imaging

Viswanathan, Naren; Venkatesh, Suresh; Schurig, David

doi:10.1109/tap.2020.3030946

Cited by 14 publications

(5 citation statements)

References 32 publications

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“…We can now define ρ′ = ρ/κ as meaningful dimensionless quantification of the noise level. Moreover, we note that considering non-zero-mean Gaussian distributions would yield the same results in our system model due to (i) the abovementioned normalization of the measured data before it is fed into the digital layers and (ii) the fact that we assume lossless analog-to-digital conversion [25], which is effectively available, for instance, with commercially available vector network analyzers in the microwave domain.…”

Section: 3mentioning

confidence: 94%

Noise-Adaptive Intelligent Programmable Meta-Imager

Qian

Hougne

2022

Intell Comput

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We present an intelligent programmable computational meta-imager that tailors its sequence of coherent scene illuminations not only to a specific information-extraction task (e.g., object recognition) but also adapts to different types and levels of noise. We systematically study how the learned illumination patterns depend on the noise, and we discover that trends in intensity and overlap of the learned illumination patterns can be understood intuitively. We conduct our analysis based on an analytical coupled-dipole forward model of a microwave dynamic metasurface antenna (DMA); we formulate a differentiable end-to-end information-flow pipeline comprising the programmable physical measurement process including noise as well as the subsequent digital processing layers. This pipeline allows us to jointly inverse-design the programmable physical weights (DMA configurations that determine the coherent scene illuminations) and the trainable digital weights. Our noise-adaptive intelligent meta-imager outperforms the conventional use of pseudo-random illumination patterns most clearly under conditions that make the extraction of sufficient task-relevant information challenging: latency constraints (limiting the number of allowed measurements) and strong noise. Programmable microwave meta-imagers in indoor surveillance and earth observation will be confronted with these conditions.

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Section: 3mentioning

confidence: 94%

Noise-Adaptive Intelligent Programmable Meta-Imager

Qian

Hougne

2022

Intell Comput

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“…Dynamic co‐optimization of both of these aspects can result in new design strategies, algorithms, image acquisition methodologies and a different trade‐off space. [ 28 ] Here, we demonstrate one possible configuration with a modified Waterbomb origami surface that can mount rigid metasurface EM tiles on panels connected with flexible hinges supporting multiple deformation stable modes. In particular, we exploit surface topology modification across unstretched, stretched, and spherically curved surfaces, and combine with near‐orthogonal modes from the metasurface panels across 17–27 GHz to demonstrate both 2D and 3D diffraction‐limited image reconstructions with adaptive imaging metrics in terms of signal‐to‐noise ratio, cross‐range resolution, and field‐of‐view.…”

Section: Conclusion and Future Outlookmentioning

confidence: 99%

“…Much progress has been made in computational imaging with sparse multi‐static metasurface radiators for diversity, [ 1 , 19 ] efficient broadband radiating elements [ 4 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ] and optimization of the overall sparse array through numerical metric‐constrained optimization and physics‐based analytical approaches. [ 27 , 28 ] As a result of these physical attributes of the EM apertures, new frontier of interesting demonstrations in phased array technology for wireless communications and RF power transfer have emerged. [ 29 , 30 , 31 , 32 , 33 , 34 ] In recent years, there have been demonstrations exploiting deep neural networks, artificial intelligence, and machine learning approaches for image feature extraction and faster/improved image reconstructions.…”

Section: Introductionmentioning

confidence: 99%

Origami Microwave Imaging Array: Metasurface Tiles on a Shape‐Morphing Surface for Reconfigurable Computational Imaging

Venkatesh

Sturm

et al. 2022

Advanced Science

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Origami is the art of paper folding that allows a single flat piece of paper to assume different 3D shapes depending on the fold patterns and the sequence of folding. Using the principles of origami along with computation imaging technique the authors demonstrate a versatile shape‐morphing microwave imaging array with reconfigurable field‐of‐view and scene‐adaptive imaging capability. Microwave/millimeter‐wave based array imaging systems are expected to be the workhorse for sensory perception of future autonomous intelligent systems. The imaging capability of a planar array‐based systems operating in complex scattering conditions have limited field‐of‐view and lack the ability to adaptively reconfigure resolution. To overcome this, here, deviations from planarity and isometry are allowed, and a shape‐morphing computational imaging system is demonstrated. Implemented on a reconfigurable Waterbomb origami surface with 22 active metasurface panels that radiate near‐orthogonal modes across 17–27 GHz, capability to image complex 3D objects in full details minimizing the effects of specular reflections in diffraction‐limited sparse imaging with scene adaptability, reconfigurable cross‐range resolution, and field‐of‐view is demonstrated. Such electromagnetic origami surfaces, through simultaneous surface shape‐morphing ability (potentially with shape‐shifting electronic materials) and electromagnetic field programmability, opens up new avenues for intelligent and robust sensing and imaging systems for a wide range of applications.

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“…Unconventional architectures [11], such as thinned [12] [13], sparse [14] [15], and clustered [16]- [35] arrays, have been recently considered to yield a suitable compromise between performance and costs. In such a framework, tiled PAs (i.e., clustered PAs composed by one or few elementary building-blocks) are gaining more and more attention thanks to their modularity that makes the whole antenna system, including the feeding network and the base-band layer, easier to fabricate and to maintain as well as controllable with a reduced number of TRMs or digital channels by using a single output/input for all the radiating elements clustered in a tile [22]- [35].…”

Section: Introductionmentioning

confidence: 99%

A Self-Replicating Single-Shape Tiling Technique for the Design of Highly Modular Planar Phased Arrays -- The Case of L-Shaped Rep-Tiles

Anselmi¹,

Tosi²,

Rocca³

et al. 2022

Preprint

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The design of irregular planar phased arrays (PAs) characterized by a highly-modular architecture is addressed. By exploiting the property of self-replicating tile shapes, also known as rep-tiles, the arising array layouts consist of tiles having different sizes, but equal shape, all being generated by assembling a finite number of smaller and congruent copies of a single elementary building-block. Towards this end, a deterministic optimization strategy is used so that the arising rep-tile arrangement of the planar PA is an optimal trade-off between complexity, costs, and fitting of user-defined requirements on the radiated power pattern, while guaranteeing the complete overlay of the array aperture. As a representative instance, such a synthesis method is applied to tile rectangular apertures with L-shaped tromino tiles.A set of representative results, concerned with ideal and real antenna models, as well, is reported for validation purposes, but also to point out the possibility/effectiveness of the proposed approach, unlike state-of-the-art tiling techniques, to reliably handle large-size array apertures.

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Optimization of a Sparse Aperture Configuration for Millimeter-Wave Computational Imaging

Cited by 14 publications

References 32 publications

Noise-Adaptive Intelligent Programmable Meta-Imager

Noise-Adaptive Intelligent Programmable Meta-Imager

Origami Microwave Imaging Array: Metasurface Tiles on a Shape‐Morphing Surface for Reconfigurable Computational Imaging

A Self-Replicating Single-Shape Tiling Technique for the Design of Highly Modular Planar Phased Arrays -- The Case of L-Shaped Rep-Tiles

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