Fractional power-based optimized consensus Kalman filtering algorithm

Shiyao Bian; Bing Wang; Yuquan Chen; Wancheng Wang

doi:10.1117/12.3022790

28 March 2024 Fractional power-based optimized consensus Kalman filtering algorithm

Shiyao Bian, Bing Wang, Yuquan Chen, Wancheng Wang

Proceedings Volume 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023); 130910F (2024) https://doi.org/10.1117/12.3022790
Event: Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 2023, Xi’an, China

Abstract

In order to improve the convergence speed, stability and state estimation accuracy of the traditional consensus Kalman filter algorithm, this paper proposes a consensus Kalman filter optimization algorithm based on fractional powers, that is, on the basis of the traditional consensus Kalman filter algorithm, fractional powers are introduced into the local Kalman filter part and the consensus fusion part respectively. The two better fractional power values are selected respectively and added to the traditional consensus Kalman filter algorithm at the same time. Through simulation experiments, it is validated that adjusting the fractional powers can notably expedite the convergence speed. Additionally, introducing fractional powers into the Kalman filtering process can also smooth error curves, enhancing stability and estimation accuracy. In comparison to introducing fractional powers separately in the Kalman filtering part and consensus fusion part, simultaneously introducing appropriate fractional powers in both parts demonstrates superior performance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shiyao Bian, Bing Wang, Yuquan Chen, and Wancheng Wang "Fractional power-based optimized consensus Kalman filtering algorithm", Proc. SPIE 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 130910F (28 March 2024); https://doi.org/10.1117/12.3022790

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