Liu, X., Lyu, C., Soleymani, S. et al. (2 more authors) (2023) Joint sensor scheduling and target tracking with efficient Bayesian optimisation. In: 2023 Sensor Signal Processing for Defence (SSPD) Proceedings. 2023 Sensor Signal Processing for Defence Conference (SSPD), 12-13 Sep 2023, Edinburgh, Scotland. Institute of Electrical and Electronics Engineers (IEEE) ISBN 979-8-3503-3732-7
Abstract
The received signal strength measurement has been widely used in search and tracking applications and its benefit is linked with the distance between the transmitter and receiver. This paper proposes an online Bayesian optimisation-based approach that relies on signal strength measurements to schedule multiple sensors for searching and tracking a moving target, without any prior knowledge of the target’s state or motion model. A unique contribution lies in incorporating the Gaussian processes factorisation method into the Bayesian optimisation framework, which enhances the effectiveness of the proposed approach. Numerical results obtained from different sizes of measurements demonstrate that the proposed approach can efficiently schedule two unmanned aerial vehicles. Particularly, it achieves at most 21% lower computational time for deciding measurement locations and 79% lower time for updating the surrogate model as compared to the benchmark approach.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. Except as otherwise noted, this author-accepted version of a paper published in 2023 Sensor Signal Processing for Defence Conference (SSPD) proceedings is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Active sensing; Bayesian optimisation; factorised Gaussian process; target tracking; sensor management; unmanned aerial vehicles; hierarchical off-diagonal low-rank (HODLR) factorisation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number UNITED STATES DEPARTMENT OF DEFENSE UNSPECIFIED |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Jul 2023 10:50 |
Last Modified: | 11 Oct 2023 08:31 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/SSPD57945.2023.10256951 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:201573 |