Detection of weak transient signals using a broadband subspace approach

Weiss, Stephan and Delaosa, Connor and Matthews, James and Proudler, Ian K. and Jackson, Ben A.; (2021) Detection of weak transient signals using a broadband subspace approach. In: 2021 Sensor Signal Processing for Defence Conference (SSPD). IEEE, GBR. ISBN 9781665433150 (https://doi.org/10.1109/SSPD51364.2021.9541472)

[thumbnail of Weiss-etal-SSPD-2021-Detection-of-weak-transient-signals-using-a-broadband-subspace-approach]
Preview
 Text. Filename: Weiss_etal_SSPD_2021_Detection_of_weak_transient_signals_using_a_broadband_subspace_approach.pdf
Accepted Author Manuscript
Download (223kB)| Preview

Abstract

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.

ORCID iDs

Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206, Delaosa, Connor, Matthews, James, Proudler, Ian K. and Jackson, Ben A.;
CORE (COnnecting REpositories)