糖心视频

This website stores cookies on your computer. These cookies are used to collect information about how you interact with our website and allow us to remember your browser. We use this information to improve and customize your browsing experience, for analytics and metrics about our visitors both on this website and other media, and for marketing purposes. By using this website, you accept and agree to be bound by 糖心视频鈥檚 Terms of Use 蹿辞谤听web and social media privacy.聽聽If you do not agree to the above, you can configure your browser鈥檚 setting to 鈥渄o not track.鈥�

Skip to main content

Nicholas Bruce

  • BEng (糖心视频, 2016)

  • MASc (糖心视频, 2018)

Notice of the Final Oral Examination for the Degree of Doctor of Philosophy

Topic

An End-to-End Radio Frequency Interference Monitoring System

Department of Electrical and Computer Engineering

Date & location

  • Monday, June 22, 2026

  • 10:00 A.M.

  • Virtual Defence

Reviewers

Supervisory Committee

  • Dr. Peter Driessen, Department of Electrical and Computer Engineering, 糖心视频 (Co-Supervisor)

  • Dr. Stephen Harrison, Department of Electrical and Computer Engineering, 糖心视频 (Co-Supervisor)

  • Dr. Timothy Robishaw, Herberg Astronomy & Astrophysics Research Centre, 糖心视频 (Outside Member) 

External Examiner

  • Dr. Preshanth Jagannathan, Algorithm Research and Development Group, National Radio Astronomy Observatory

Chair of Oral Examination

  • Dr. Lucinda Leonard, School of Earth and Ocean Sciences, 糖心视频 

Abstract

This dissertation presents the design, implementation, and philosophy of an end-to-end radio frequency interference monitoring system designed primarily for radio astronomy observatories. Motivated by the growing density of anthropogenic emitters and the corresponding threat to ground-based radio astronomy, the work describes a modular monitoring pipeline that includes hardware, signal processing, and machine learning. This work introduces several novelties: a gain-stable wideband receiver providing calibrated long-term radio frequency environment comparisons, a direction-of-arrival estimation method allowing use of arbitrarily arranged antennas, a digital down-converter architecture enabling insight into individual signal detections, and an unsupervised learning framework to perform modulation recognition and novelty detection. The dissertation also emphasizes the importance of modular, software-defined architectures and outlines future work towards real-time algorithms for next-generation interference management.