Submillimeter-wave holograms and imaging neural network : Experiments at 220-330 GHz
Loading...
Access rights
openAccess
publishedVersion
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Date
Major/Subject
Mcode
Degree programme
Language
en
Pages
7
Series
PASSIVE AND ACTIVE MILLIMETER-WAVE IMAGING XXV, Proceedings of SPIE ; Volume 12111
Abstract
We present the experimental results of a submillimeter-wave standoff imaging system based on a frequency-diverse hologram and image reconstruction via machine learning at 220-330 GHz. The imaging system operates in a single-pixel, monostatic configuration consisting of a transceiver together with a frequency-diverse phase hologram to interrogate the region of interest with quasirandom field patterns. The spatial reflectivity distribution in the region of interest is embedded in the wide-band frequency spectrum of the back-reflected signal and the images are acquired without mechanical or electrical scanning. Images from a visible-light camera are used as the ground truth of the target elements. The targets are scanned in the region of interest, while the wide-band reflection spectrum for the target is measured. The collected imagesignal pair data are used to train a deconvolutional neural network for image reconstruction with the submillimeter-wave reflection spectra as input. In experiments, a corner-cube reflector and a complex test target made of copper foam were imaged in a 28-degree field of view at a distance of 600 mm from the imaging system. The effect of bandwidth on image quality is evaluated using 10-40 GHz bandwidths centered at 275 GHz to image the copper foam target. The resolution in the image predictions was estimated from fitted point-spread functions to be from 12 mm to 30 mm, with the highest resolution at the broadest bandwidth. We have correlated the measured field patterns at the region of interest with the mean squared error (MSE) of the predicted corner-cube images to analyze the effect of field characteristics on imaging accuracy. The results demonstrate increased accuracy in locations with high electric field amplitude and variation over the imaging bandwidth.Description
Keywords
Other note
Citation
Palli, S-V, Hiltunen, P, Kosonen, M, Tamminen, A, Ala-Laurinaho, J & Taylor, Z 2022, Submillimeter-wave holograms and imaging neural network : Experiments at 220-330 GHz. in DA Wikner & DA Robertson (eds), PASSIVE AND ACTIVE MILLIMETER-WAVE IMAGING XXV. Proceedings of SPIE, vol. 12111, SPIE, Passive and Active Millimeter-Wave Imaging, Orlando, Florida, United States, 03/04/2022. https://doi.org/10.1117/12.2618274