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

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorPalli, Samu-Villeen_US
dc.contributor.authorHiltunen, Paavoen_US
dc.contributor.authorKosonen, Millaen_US
dc.contributor.authorTamminen, Aleksien_US
dc.contributor.authorAla-Laurinaho, Juhaen_US
dc.contributor.authorTaylor, Zacharyen_US
dc.contributor.departmentZachary Taylor Groupen_US
dc.contributor.departmentDepartment of Electronics and Nanoengineeringen_US
dc.contributor.editorWikner, DAen_US
dc.contributor.editorRobertson, DAen_US
dc.date.accessioned2023-02-01T09:10:01Z
dc.date.available2023-02-01T09:10:01Z
dc.date.issued2022en_US
dc.description.abstractWe 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.en
dc.description.versionPeer revieweden
dc.format.extent7
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationPalli , 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/10.1117/12.2618274en
dc.identifier.doi10.1117/12.2618274en_US
dc.identifier.isbn978-1-5106-5098-5
dc.identifier.issn0277-786X
dc.identifier.issn1996-756X
dc.identifier.otherPURE UUID: 1238337a-f325-4b30-acb7-a637a6e851dcen_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/1238337a-f325-4b30-acb7-a637a6e851dcen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/99115552/1211109.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/119518
dc.identifier.urnURN:NBN:fi:aalto-202302011868
dc.language.isoenen
dc.publisherSPIE-INT SOC OPTICAL ENGINEERING
dc.relation.ispartofPassive and Active Millimeter-Wave Imagingen
dc.relation.ispartofseriesPASSIVE AND ACTIVE MILLIMETER-WAVE IMAGING XXVen
dc.relation.ispartofseriesProceedings of SPIEen
dc.relation.ispartofseriesVolume 12111en
dc.rightsopenAccessen
dc.subject.keywordHologramen_US
dc.subject.keywordimagingen_US
dc.subject.keywordneural networken_US
dc.subject.keywordsubmillimeter-waveen_US
dc.subject.keywordMILLIMETERen_US
dc.subject.keywordRADARen_US
dc.titleSubmillimeter-wave holograms and imaging neural network : Experiments at 220-330 GHzen
dc.typeConference article in proceedingsfi
dc.type.versionpublishedVersion
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