Li, Wenda;
Tang, Chong;
Vishwakarma, Shelly;
Woodbridge, Karl;
Chetty, Kevin;
(2022)
Design of High-Speed Software Defined Radar with GPU Accelerator.
IET Radar, Sonar and Navigation
10.1049/rsn2.12244.
(In press).
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Abstract
Software defined radar (SDRadar) systems have become an important area for future radar development and are based on similar concepts to Software defined radio (SDR). Most of the processing like filtering, frequency conversion and signal generation are implemented in software. Currently, radar systems tend to have complex signal processing and operate at wider bandwidth, which means that limits on the available computational power must be considered when designing a SDRadar system. This paper presents a feasible solution to this potential limitation by accelerating the signal processing using a GPU to enable the development of a high speed SDRadar system. The developed system overcomes the limitation on the processing speed by CPU-only, and has been tested on three different SDR devices. Results show that, with GPU accelerator, the processing rate can achieve up to 80 MHz compared to 20 MHz with the CPU-only. The high speed processing makes it possible to run in real-time and process full bandwidth across the WiFi signal acquired by multiple channels. The gains made through porting the processing to the GPU moves the technology towards real-world application in various scenarios ranging from healthcare to IoT, and other applications that required significant computational processing.
Type: | Article |
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Title: | Design of High-Speed Software Defined Radar with GPU Accelerator |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1049/rsn2.12244 |
Publisher version: | https://doi.org/10.1049/rsn2.12244 |
Language: | English |
Additional information: | Copyright © 2022 The Authors. IET Radar, Sonar & Navigation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
URI: | https://discovery.ucl.ac.uk/id/eprint/10144057 |
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