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

• Published in: Journal of physics. Conference series Vol. 2898; no. 1; pp. 12029 - 12034
• Main Authors: Li, Na, Zou, Lei, Wang, Chenxi
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.11.2024
• Subjects: Binary codes; Difference equations; Estimates; Failure; Filtration; Multisensor fusion; Parameter estimation; Random variables; Signal distortion; Statistical analysis
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/2898/1/012029

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.