Submillimeter-wave holograms and imaging neural network: experiments at 220-330 GHz

Samu-Ville Pälli; Paavo Hiltunen; Milla Kosonen; Aleksi Tamminen; Juha Ala-Laurinaho; Zachary Taylor

doi:10.1117/12.2618274

3 June 2022 Submillimeter-wave holograms and imaging neural network: experiments at 220-330 GHz

Samu-Ville Pälli, Paavo Hiltunen, Milla Kosonen, Aleksi Tamminen, Juha Ala-Laurinaho, Zachary Taylor

Author Affiliations +

Proceedings Volume 12111, Passive and Active Millimeter-Wave Imaging XXV; 1211109 (2022) https://doi.org/10.1117/12.2618274
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

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 quasi-random 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 image-signal 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.

Conference Presentation

Citation Download Citation

Samu-Ville Pälli, Paavo Hiltunen, Milla Kosonen, Aleksi Tamminen, Juha Ala-Laurinaho, and Zachary Taylor "Submillimeter-wave holograms and imaging neural network: experiments at 220-330 GHz", Proc. SPIE 12111, Passive and Active Millimeter-Wave Imaging XXV, 1211109 (3 June 2022); https://doi.org/10.1117/12.2618274

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE