Abstract: Terahertz (THz) imaging holds promise in a wide range of application fields due to the penetration ability of THz radiation, in combination with a relatively low wavelength, as compared to radar, which facilitates generating sharp images. However, existing THz imaging techniques typically rely on sequential scanning due to the unavailability of large detector arrays. The use of Compressive Sensing (CS) techniques can reduce the number of measurements but does not solve its sequential acquisition. In this work, we show the feasibility of single-shot THz 3D imaging leveraging a multi-aperture THz camera. Adopting a CS perspective, we construct a linear sensing model and assume target sparsity. Our experimental validation confirms that sparsity-promoting methods succeed in reconstructing 3D volumes from a few intensity measurements.

Acknowledgement: This work received partial funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 101019972; grant ID: https://doi.org/10.3030/101019972; Crossref Funder ID https://doi.org/10.13039/100010662).

This document is the accepted manuscript version that has been published in final form in:

2024 International Workshop on the Theory of Computational Sensing and its Applications to Radar, Multimodal Sensing and Imaging (CoSeRa), DOI: https://doi.org/10.1109/CoSeRa60846.2024.10720381

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