Enhanced Space-Time Covariance Estimation Based on a System Identification Approach

The error inflicted on a space-time covariance estimate due to the availability of only finite data is known to perturb the eigenvalues and eigenspaces of its z-domain equivalent, i.e., the cross-spectral density matrix. In this paper, we show that a significantly more accurate estimate can be obtai...

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Bibliographic Details
Published in2022 Sensor Signal Processing for Defence Conference (SSPD) pp. 1 - 5
Main Authors Khattak, Faizan A., Proudler, Ian K., Weiss, Stephan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2022
Subjects
Data models
Eigenvalues and eigenfunctions
Estimation
Signal processing
Signal to noise ratio
System identification
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DOI10.1109/SSPD54131.2022.9896183

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Summary:The error inflicted on a space-time covariance estimate due to the availability of only finite data is known to perturb the eigenvalues and eigenspaces of its z-domain equivalent, i.e., the cross-spectral density matrix. In this paper, we show that a significantly more accurate estimate can be obtained if the source signals driving the signal model are also accessible, such that a system identication approach for the source model becomes viable. We demonstrate this improved accuracy in simulations, and discuss its dependencies on the sample size and the signal to noise ratio of the data.
DOI:10.1109/SSPD54131.2022.9896183