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Real-time Radar Signal Processing on Massively Parallel Processor Arrays
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).ORCID-id: 0000-0002-4932-4036
Saab AB, Gothenburg, Sweden.
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).ORCID-id: 0000-0001-6625-6533
2013 (engelsk)Inngår i: Conference Record of The Forty-Seventh Asilomar Conference on Signals, Systems & Computers: November 3–6, 2013 Pacific Grove, California / [ed] Michael B. Matthews, Piscataway, NJ: IEEE Signal Processing Society, 2013, 1810-1814 s.Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The next generation radar systems have high performance demands on the signal processing chain. Among these are advanced image creating sensor systems in which complex calculations are to be performed on huge sets of data in realtime. Massively Parallel Processor Arrays (MPPAs) are gaining attention to cope with the computational requirements of complex radar signal processing by exploiting the massive parallelism inherent in the algorithms in an energy efficient manner.

In this paper, we evaluate two such massively parallel architectures, namely, Ambric and Epiphany, by implementing a significantly large case study of autofocus criterion calculation, which is a key component in future synthetic aperture radar systems. The implementation results from the two case studies are compared on the basis of achieved performance, energy efficiency, and programmability. ©2013 IEEE.

sted, utgiver, år, opplag, sider
Piscataway, NJ: IEEE Signal Processing Society, 2013. 1810-1814 s.
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-24017DOI: 10.1109/ACSSC.2013.6810614ISBN: 978-1-4799-2390-8 (digital)ISBN: 978-1-4799-2388-5 (digital)OAI: oai:DiVA.org:hh-24017DiVA: diva2:667711
Konferanse
47th IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, November 3–6, 2013
Prosjekter
JUMP (JUmp to Manycore Platforms)
Forskningsfinansiär
Knowledge Foundation
Merknad

The authors would like to thank Nethra Imaging Inc. and Adapteva Inc. for giving access to their software development suite and hardware board. This research is done in the JUMP (JUmp to Manycore Platforms) project within the CERES research program supported by the Knowledge Foundation in cooperation with Saab AB.

Tilgjengelig fra: 2013-11-27 Laget: 2013-11-27 Sist oppdatert: 2017-04-10bibliografisk kontrollert

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