Advanced GNSS-R signals processing with GPUs
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hdl:2117/329153
Document typeArticle
Defense date2020-01-01
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
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is licensed under a Creative Commons license
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Attribution-NonCommercial-NoDerivs 3.0 Spain
ProjectTECNICAS AVANZADAS EN TELEDETECCION APLICADA USANDO SEÑALES GNSS Y OTRAS SEÑALES DE OPORTUNIDAD (MINECO-ESP2015-70014-C2-1-R)
SENSING WITH PIONEERING OPPORTUNISTIC TECHNIQUES (AEI-RTI2018-099008-B-C21)
SENSING WITH PIONEERING OPPORTUNISTIC TECHNIQUES (AEI-RTI2018-099008-B-C21)
Abstract
Global navigation satellite system reflectometry (GNSS-R) is a group of techniques that uses satellite navigation signals as signals of opportunity for remote sensing applications. In GNSS-R, large amounts of data are acquired and have to be processed. Computation time is typically the bottleneck for ground and airborne experiments. This article presents an efficient solution for off-line GNSS-R processing data taking advantage of graphics processing units (GPUs). After comparing to the typically used CPU languages, such as MATLAB and C++, the advantage of using parallel processing on the GPU is clear. GPU-based computation can reduce the processing time by as much as 95% of the acquisition time of the data. An implementation taking advantage of a home-use GPU is proposed for the data processing units. Thanks to its efficiency, even real-time processing experiments are feasible.
CitationCervelló, O. [et al.]. Advanced GNSS-R signals processing with GPUs. "IEEE journal of selected topics in applied earth observations and remote sensing", 1 Gener 2020, vol. 13, p. 1158-1163.
ISSN1939-1404
Publisher versionhttps://ieeexplore.ieee.org/document/9028131
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