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Autofocusing of THz SAR Images by Integrating Compressed Sensing into the Backprojection Process
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-3928-6064
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0003-3945-8951
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312X
2023 (English)In: Proceedings of the IEEE Radar Conference, Institute of Electrical and Electronics Engineers (IEEE), 2023, Vol. 2023Conference paper, Published paper (Refereed)
Abstract [en]

The THz frequency spectrum provides an opportunity to explore high-resolution synthetic-aperture-radar (SAR) short-range imaging that can be used for various applications. However, the performance of THz SAR imaging is sensitive to phase errors that can be caused by an insufficient amount of data samples for image formation and by path deviations that can be practically caused by SAR platform vibrations, changes in speed, changes in direction, and acceleration. To solve the former problem, an improved interpolation procedure for backprojection algorithms has been proposed. However, to make these algorithms efficient in handling the latter problem, an additional autofocusing is necessary. In this paper, we introduce an autofocusing procedure based on compressed sensing that is incorporated into the backprojection algorithm. The reconstruction is based on the following calculated parameters: windowed interpolation sinc kernel, and range distances between SAR platform and image pixels in a defined image plane. The proposed approach is tested on real data, which was acquired by the 2\pi FMCW SAR system through outdoor SAR imaging. © 2023 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023. Vol. 2023
Series
IEEE International Conference on Radar (RADAR), ISSN 1097-5764, E-ISSN 2640-7736
Keywords [en]
Autofocusing, Compressed Sensing, FMCW SAR, THz, Frequency modulation, Interpolation, Radar imaging, Synthetic aperture radar, Terahertz waves, Auto-focusing, Backprojection algorithms, Backprojections, Compressed-Sensing, FMCW synthetic-aperture-radar, Frequency spectra, Synthetic aperture radar images, Synthetic aperture radar imaging, THz frequencies
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-25226DOI: 10.1109/RadarConf2351548.2023.10149760ISI: 001031599600217Scopus ID: 2-s2.0-85163791710ISBN: 9781665436694 (print)OAI: oai:DiVA.org:bth-25226DiVA, id: diva2:1786045
Conference
2023 IEEE Radar Conference, RadarConf23, San Antonia, 1 May through 5 May 2023
Projects
Multistatic High-resolution Sensing at THz, Project-ID A17
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsAvailable from: 2023-08-07 Created: 2023-08-07 Last updated: 2023-08-24Bibliographically approved

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Ivanenko, YevhenVu, Viet ThuyPettersson, Mats

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