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The Challenge of Onboard SAR Processing: A GPU Opportunity

Data acquired by a Synthetic Aperture Radar (SAR), onboard a satellite or an airborne platform, must be processed to produce a visible image. For this reason, data must be transferred to the ground station and processed through a time/computing-consuming focusing algorithm. Thanks to the advances in...

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Detalles Bibliográficos
Autores principales: Romano, Diego, Mele, Valeria, Lapegna, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304007/
http://dx.doi.org/10.1007/978-3-030-50420-5_4
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author Romano, Diego
Mele, Valeria
Lapegna, Marco
author_facet Romano, Diego
Mele, Valeria
Lapegna, Marco
author_sort Romano, Diego
collection PubMed
description Data acquired by a Synthetic Aperture Radar (SAR), onboard a satellite or an airborne platform, must be processed to produce a visible image. For this reason, data must be transferred to the ground station and processed through a time/computing-consuming focusing algorithm. Thanks to the advances in avionic technology, now GPUs are available for onboard processing, and an opportunity for SAR focusing opened. Due to the unavailability of avionic platforms for this research, we developed a GPU-parallel algorithm on commercial off-the-shelf graphics cards, and with the help of a proper scaling factor, we projected execution times for the case of an avionic GPU. We evaluated performance using ENVISAT (Environmental Satellite) ASAR Image Mode level 0 on both NVIDIA Kepler and Turing architectures.
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spelling pubmed-73040072020-06-19 The Challenge of Onboard SAR Processing: A GPU Opportunity Romano, Diego Mele, Valeria Lapegna, Marco Computational Science – ICCS 2020 Article Data acquired by a Synthetic Aperture Radar (SAR), onboard a satellite or an airborne platform, must be processed to produce a visible image. For this reason, data must be transferred to the ground station and processed through a time/computing-consuming focusing algorithm. Thanks to the advances in avionic technology, now GPUs are available for onboard processing, and an opportunity for SAR focusing opened. Due to the unavailability of avionic platforms for this research, we developed a GPU-parallel algorithm on commercial off-the-shelf graphics cards, and with the help of a proper scaling factor, we projected execution times for the case of an avionic GPU. We evaluated performance using ENVISAT (Environmental Satellite) ASAR Image Mode level 0 on both NVIDIA Kepler and Turing architectures. 2020-05-22 /pmc/articles/PMC7304007/ http://dx.doi.org/10.1007/978-3-030-50420-5_4 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Romano, Diego
Mele, Valeria
Lapegna, Marco
The Challenge of Onboard SAR Processing: A GPU Opportunity
title The Challenge of Onboard SAR Processing: A GPU Opportunity
title_full The Challenge of Onboard SAR Processing: A GPU Opportunity
title_fullStr The Challenge of Onboard SAR Processing: A GPU Opportunity
title_full_unstemmed The Challenge of Onboard SAR Processing: A GPU Opportunity
title_short The Challenge of Onboard SAR Processing: A GPU Opportunity
title_sort challenge of onboard sar processing: a gpu opportunity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304007/
http://dx.doi.org/10.1007/978-3-030-50420-5_4
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