Development of Quantum Enabled Staring Radar with Low Phase Noise

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Staring radar provide a significant capability against the detection of low observable targets such as drones and birds. Their performance in strong urban clutter can be impacted by system limitations due to phase noise resulting from imperfections in the reference oscillator. This paper describes a new class of Quantum oscillator that can provide an alternative clock reference signal for the staring radar which can lower the phase noise and improve sensitivity against strong clutter at low frequencies. Preliminary results are presented to baseline empirical measurement of the staring radar in urban clutter as a precursor to the integration with the Quantum oscillator.

Original languageEnglish
Title of host publication2021 18th European Radar Conference (EuRAD)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Electronic)9782874870651
ISBN (Print)9781665447232 (PoD)
Publication statusPublished - 2 Jun 2021
Event18th European Radar Conference, EuRAD 2021 - London, United Kingdom
Duration: 5 Apr 20227 Apr 2022

Publication series

NameEuropean Radar Conference (EURAD)


Conference18th European Radar Conference, EuRAD 2021
Country/TerritoryUnited Kingdom

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was in part supported by UK National Quantum Technology Hub in Sensing and Timing (Project EP/ T001046/1), European Union’s Horizon 2020 research and innovation programme (820404 – IQ clock project), and BAE Systems I-CASE PhD. Authors would also like to thank Aveillant Limited for their support with the radar system.

Publisher Copyright:
© 2022 European Microwave Association (EuMA).


  • drone detection
  • phase noise
  • reference oscillator
  • staring radar

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Instrumentation


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