AI Heterogeneous Radar Digital Back-end Platform Based on RFSoC

Enbin Wang, Zhaojian Jin, Zhifeng Ma, Deshe Wang, Qiongzhi Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the development trend of direct radio frequency sampling in radar systems, we propose an artificial intelligence (AI) heterogeneous radar digital back-end platform based on the RF System-on-Chip (RFSoC). Utilize the RFSOC's radio frequency sampling capacity, the RF signal is directly sampled and synthesized in the proposed system. Specially, the overall system is equipped with accelerated computing scheme based on AI for signal processing, which integrates the Jetson AGX Xavier series GPU to the digital back-end platform. Firstly, the overall box diagram of the system design is proposed. Secondly, the key technologies in the design are discussed. Finally, this platform also provides an important reference value for the construction of next-generation RF sampling radar and radar heterogeneous computing platform.

Original languageEnglish
Title of host publicationIEEE 6th Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2022
EditorsBing Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1885-1889
Number of pages5
ISBN (Electronic)9781665458641
DOIs
Publication statusPublished - 2022
Event6th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2022 - Beijing, China
Duration: 3 Oct 20225 Oct 2022

Publication series

NameIEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)
Volume2022-October
ISSN (Print)2689-6621

Conference

Conference6th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2022
Country/TerritoryChina
CityBeijing
Period3/10/225/10/22

Keywords

  • AI heterogeneous
  • Radar digital back-end
  • Radio Frequency System on Chip
  • radio frequency sampling
  • radio frequency synthese

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