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.

The challenge of onboard sar processing: A gpu opportunity

Romano Diego;
2020

Abstract

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
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
9783030504199
GPU-parallel
Onboard SAR focusing
Range-Doppler algorithm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/385498
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