| Autor: |
Raquel Caballero-Águila, María J. García-Ligero, Aurora Hermoso-Carazo, Josefa Linares-Pérez |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Mathematical Biosciences and Engineering, Vol 20, Iss 8, Pp 14550-14577 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1551-0018 |
| DOI: |
10.3934/mbe.2023651?viewType=HTML |
| Popis: |
This paper examines the distributed filtering and fixed-point smoothing problems for networked systems, considering random parameter matrices, time-correlated additive noises and random deception attacks. The proposed distributed estimation algorithms consist of two stages: the first stage creates intermediate estimators based on local and adjacent node measurements, while the second stage combines the intermediate estimators from neighboring sensors using least-squares matrix-weighted linear combinations. The major contributions and challenges lie in simultaneously considering various network-induced phenomena and providing a unified framework for systems with incomplete information. The algorithms are designed without specific structure assumptions and use a covariance-based estimation technique, which does not require knowledge of the evolution model of the signal being estimated. A numerical experiment demonstrates the applicability and effectiveness of the proposed algorithms, highlighting the impact of observation uncertainties and deception attacks on estimation accuracy. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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