Multi-sensor fusion estimation subject to random sensor failures under binary encoding scheme: A federated-filtering-based method

This paper explores the issue of fusion estimation in multi-sensor systems experiencing random sensor failures via a binary coding scheme (BCS). The occurrence of sensor failures is modeled using random variables with predetermined probability distributions. To avert the potential signal distortions...

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Veröffentlicht in:Journal of physics. Conference series Jg. 2898; H. 1; S. 12029 - 12034
Hauptverfasser: Li, Na, Zou, Lei, Wang, Chenxi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bristol IOP Publishing 01.11.2024
Schlagworte:
Binary codes
Difference equations
Estimates
Failure
Filtration
Multisensor fusion
Parameter estimation
Random variables
Signal distortion
Statistical analysis
ISSN:1742-6588, 1742-6596
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Zusammenfassung:This paper explores the issue of fusion estimation in multi-sensor systems experiencing random sensor failures via a binary coding scheme (BCS). The occurrence of sensor failures is modeled using random variables with predetermined probability distributions. To avert the potential signal distortions during network-based communication, the BCS is utilized to transform the measurement signals into bit strings. A novel federated-filtering-based fusion estimation approach is developed to obtain the desired state estimates. The optimal estimator parameters are achieved by solving a pair of recursive difference equations, taking into account the impacts of bit errors and probabilistic quantization. Additionally, the ultimate boundedness of the estimation error covariance for the fusion estimates is guaranteed by a sufficient condition that we establish. Finally, the utility of the introduced fusion estimation method is illustrated through a simulation example.
Bibliographie:ObjectType-Article-1
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2898/1/012029