Abstract
In this paper, the problem of state estimation over sensor networks for discrete-time linear time-varying systems with correlated noise is studied. Herein, we consider that the measurement noise of each sensor is cross-correlated with the process noise, and the measurement noise of different sensors are also cross-correlated. To estimate the system state in such a case, a consensus-based state estimation algorithm is designed. The effectiveness of the proposed filtering algorithm is further demonstrated by comparative simulations.
Original language | English |
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Title of host publication | Proceedings of 2021 IEEE International Conference on Unmanned Systems, ICUS 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 964-969 |
Number of pages | 6 |
ISBN (Electronic) | 9780738146577 |
DOIs | |
Publication status | Published - 2021 |
Externally published | Yes |
Event | 2021 IEEE International Conference on Unmanned Systems, ICUS 2021 - Beijing, China Duration: 15 Oct 2021 → 17 Oct 2021 |
Publication series
Name | Proceedings of 2021 IEEE International Conference on Unmanned Systems, ICUS 2021 |
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Conference
Conference | 2021 IEEE International Conference on Unmanned Systems, ICUS 2021 |
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Country/Territory | China |
City | Beijing |
Period | 15/10/21 → 17/10/21 |
Keywords
- Kalman consensus filter(KCF)
- correlated noise
- state estimation
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Ge, W., Zhou, J., & Niu, M. (2021). Consensus-Based State Estimation over Sensor Networks with Correlated Noise. In Proceedings of 2021 IEEE International Conference on Unmanned Systems, ICUS 2021 (pp. 964-969). (Proceedings of 2021 IEEE International Conference on Unmanned Systems, ICUS 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICUS52573.2021.9641407