Event-triggered sequential fusion estimation with correlated noises
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Published on: July 11, 2025
Liping Yan1, Lu Jiang2, Yuanqing Xia3
1Key Laboratory of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China; University of Windsor, Windsor N9B3P4, Canada.
Abstract:
This paper focuses on the event-triggered sequential fusion estimation for the multi-sensor systems with correlated noises. An event-triggered communication mechanism is introduced to reduce unnecessary energy waste. Considering that measurement noise of different sensors is correlated with each other and also correlated with the system noise of the previous step, an event-triggered sequential fusion estimation algorithm is proposed in the sense of linear minimum covariance. The standard values of the correlation parameters are defined to ensure convergence of the designed fusion algorithm and an upper bound of the estimation error covariance is given. A numerical example is used to illustrate the effectiveness of the presented fusion algorithm.
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