Design of high‐speed software defined radar with GPU accelerator

Wenda Li, Chong Tang, Shelly Vishwakarma, Karl Woodbridge, Kevin Chetty

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
64 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)1083-1094
Number of pages12
JournalIET Radar, Sonar & Navigation
Volume16
Issue number7
Early online date28 Feb 2022
DOIs
Publication statusPublished - Jul 2022

Keywords

  • GPU accelerator
  • signal processing
  • software defined radar

Fingerprint

Dive into the research topics of 'Design of high‐speed software defined radar with GPU accelerator'. Together they form a unique fingerprint.

Cite this