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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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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. |
format | Online Article Text |
id | pubmed-7304007 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
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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