Enhanced space-time covariance estimation based on a system identification approach

Khattak, Faizan A. and Proudler, Ian K. and Weiss, Stephan; (2022) Enhanced space-time covariance estimation based on a system identification approach. In: 2022 Sensor Signal Processing for Defence Conference, SSPD 2022 - Proceedings. 2022 Sensor Signal Processing for Defence Conference, SSPD 2022 - Proceedings . IEEE, GBR. ISBN 9781665483483 (https://doi.org/10.1109/SSPD54131.2022.9896183)

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Abstract

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.

ORCID iDs

Khattak, Faizan A., Proudler, Ian K. and Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206;
  • Item type:Book Section
    ID code:81544
    Dates:
    Date
    Event
    23 September 2022
    Published
    14 September 2022
    Published Online
    28 June 2022
    Accepted
    Notes:© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:21 Jul 2022 16:22
    Last modified:28 Nov 2024 01:32
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/81544
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