<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The information fusion problem is studied for multi-sensor systems in the presence of bounded disturbances. In this paper, a distributed fusion estimation algorithm is proposed based on the set-membership theory, which obtains the overall estimates based on multi-ellipsoids intersection. A parameter adaptive adjustment scheme is derived to guarantee the performance of the algorithm. The feedback mechanism is also introduced to enhance the estimation procedure. Through theoretical analysis and simulation, the performance of the proposed algorithm is analyzed, and some interesting properties of the proposed algorithm are proved. Results show that the proposed algorithm improves the point estimation accuracy. Compared with the algorithm without feedback, the one with feedback has better local estimation. Meanwhile, the effectiveness of the proposed algorithm in improving state estimation accuracy has been proved by the simulation results.</p>
</abstract>

The information fusion problem is studied for multi-sensor systems in the presence of bounded disturbances. In this paper, a distributed fusion estimation algorithm is proposed based on the set-membership theory, which obtains the overall estimates based on multi-ellipsoids intersection. A parameter adaptive adjustment scheme is derived to guarantee the performance of the algorithm. The feedback mechanism is also introduced to enhance the estimation procedure. Through theoretical analysis and simulation, the performance of the proposed algorithm is analyzed, and some interesting properties of the proposed algorithm are proved. Results show that the proposed algorithm improves the point estimation accuracy. Compared with the algorithm without feedback, the one with feedback has better local estimation. Meanwhile, the effectiveness of the proposed algorithm in improving state estimation accuracy has been proved by the simulation results.

Distributed Fusion Estimation for the Measurements with Bounded Disturbances

Measurement Science Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Distributed Fusion Estimation for the Measurements with Bounded Disturbances"}

The information fusion problem is studied for multi-sensor systems in the presence of bounded disturbances. In this paper, a distributed fusion estimation...

Distributed Fusion Estimation for the Measurements with Bounded Disturbances

Pubblicato online: 13 ott 2022

Pagine: 275 - 282

Ricevuto: 06 dic 2021

Accettato: 25 lug 2022

DOI: https://doi.org/10.2478/msr-2022-0035

Parole chiave
distributed fusion, bounded disturbances, set-membership estimation, ellipsoidal state bounding

© 2022 Qiang Shen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Distributed Fusion Estimation for the Measurements with Bounded Disturbances

Pubblicato online: 13 ott 2022

Pagine: 275 - 282

Ricevuto: 06 dic 2021

Accettato: 25 lug 2022

DOI: https://doi.org/10.2478/msr-2022-0035

Parole chiavedistributed fusion, bounded disturbances, set-membership estimation, ellipsoidal state bounding

© 2022 Qiang Shen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
distributed fusion, bounded disturbances, set-membership estimation, ellipsoidal state bounding