Detection of weak transient signals using a broadband subspace approach

Stephan Weiss, Connor Delaosa, James Matthews, Ian K. Proudler, Ben A. Jackson

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

6 Citations (Scopus)
31 Downloads (Pure)


We investigate the detection of broadband weak transient signals by monitoring a projection of the measurement data onto the noise-only subspace derived from the stationary sources. This projection utilises a broadband subspace decomposition of the data's space-time covariance matrix. The energy in this projected 'syndrome' vector is more discriminative towards the presence or absence of a transient signal than the original data, and can be enhanced by temporal averaging. We investigate the statistics, and indicate in simulations how discrimination can be traded off with the time to reach a decision, as well as with the sample size over which the space-time covariance is estimated.
Original languageEnglish
Title of host publication2021 Sensor Signal Processing for Defence Conference (SSPD)
Place of PublicationPiscataway, NJ.
Number of pages5
ISBN (Print)9781665433150
Publication statusPublished - 15 Sept 2021
EventInternational Conference in Sensor Signal Processing for Defence: from Sensor to Decision - Edinburgh, United Kingdom
Duration: 14 Sept 202115 Sept 2021
Conference number: 10


ConferenceInternational Conference in Sensor Signal Processing for Defence
Abbreviated titleSSPD
Country/TerritoryUnited Kingdom
Internet address


  • detection
  • weak transient signals
  • broadband
  • subspace


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