Unscented Kalman filter of graph signals. (February 2023)
- Record Type:
- Journal Article
- Title:
- Unscented Kalman filter of graph signals. (February 2023)
- Main Title:
- Unscented Kalman filter of graph signals
- Authors:
- Li, Wenling
Fu, Xiaoyan
Zhang, Bin
Liu, Yang - Abstract:
- Abstract: We consider the nonlinear filtering problem of graph signals, where the measurements are generated based on graph topology. We propose a graph-based unscented Kalman filter (UKF) by using the decomposition of graph Laplacian matrix in the design of Kalman gain matrix. We demonstrate that the graph-based UKF reduces to the UKF for the graph Fourier transform of signals with a diagonal Kalman gain matrix, so that each vertex signal can be updated independently and more accurate results can be derived to reduce accumulation errors. Simulation results are provided to verify the effectiveness of the proposed filter.
- Is Part Of:
- Automatica. Volume 148(2023)
- Journal:
- Automatica
- Issue:
- Volume 148(2023)
- Issue Display:
- Volume 148, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 148
- Issue:
- 2023
- Issue Sort Value:
- 2023-0148-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-02
- Subjects:
- Graph filter -- Nonlinear filter -- UKF
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Automation -- Periodicals
629.805 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00051098 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.automatica.2022.110796 ↗
- Languages:
- English
- ISSNs:
- 0005-1098
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1829.450000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25310.xml