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Factorized Geometrical Autofocus for UWB UHF-Band SAR With a GPS-Supported Linear Track Model
J. Torgrimsson Konsult, Gothenburg, Sweden.
Saab Ab, Stockholm, Sweden; Chalmers University Of Technology, Gothenburg, Sweden.
Halmstad University, School of Information Technology. Saab Ab, Stockholm, Sweden.
Chalmers University Of Technology, Gothenburg, Sweden; Swedish Defence Research Agency, Stockholm, Sweden.ORCID iD: 0000-0001-5757-9517
2022 (English)In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, E-ISSN 1557-9603, Vol. 58, no 4, p. 3147-3161Article in journal (Refereed) Published
Abstract [en]

This article describes how to form a SAR image without proper motion quantities. That is within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a fast-factorized back-projection formulation with adjustable geometry parameters. Subapertures are tuned and merged pair-by-pair (base-2) and step-by-step. With this technique, we can correct an erroneous geometry and form a focused image. The FGA algorithm has been applied on two datasets, acquired by the UWB CARABAS 3 system at UHF-band. The tracks are measured accurately by means of a DGPS. We however adopt and modify a geometry model. Equidistant linear tracks at fixed altitudes are assumed. These tracks are then regulated via a two-stage search strategy and a reverseprocessing procedure. As this is a first experiment at UHF-band, we provide GPS-based length values for the subapertures, to simplify the search. Multiple geometry solutions are tested for each subaperture pair, i.e., at each resolution level. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a focused image with wavelength resolution at UHF-band, i.e., with minimum support from a motion measurement system. © 1965-2011 IEEE.

Place, publisher, year, edition, pages
Piscataway: IEEE, 2022. Vol. 58, no 4, p. 3147-3161
Keywords [en]
Autofocus, back-projection, factorized geometrical autofocus (FGA), synthetic aperture radar (SAR)
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:hh:diva-50033DOI: 10.1109/TAES.2022.3149235ISI: 000838710200040Scopus ID: 2-s2.0-85124725941OAI: oai:DiVA.org:hh-50033DiVA, id: diva2:1741524
Funder
VinnovaAvailable from: 2023-03-06 Created: 2023-03-06 Last updated: 2023-03-06Bibliographically approved

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Hellsten, Hans

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