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Remote State Estimation in Networked Systems: Data Pre-Processing or Not?
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DOI：10.1109/TNSE.2023.3275971.png)
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Abstract
En 中文
In a networked system, a wireless sensor measures the state of a process or system, and then sends the measurement data to a remote state estimator via a communication channel. Recently, there has been extensive research on using data pre-processing methods to improve the estimation performance subject to communication constraints. However, in practical applications, additional data pre-processing and the involved computation lead to time delays, which affect the estimation performance. In this article, we investigate the use of two data pre-processing methods (namely, a smart sensor and an event-triggered mechanism) in comparison to a standard raw data transmission scheme. We analyze the resulting tradeoff relationship through addressing the benefits brought by data pre-processing and the impact of its induced time delays. In addition, we provide threshold-based structures of the tradeoff for both methods, and demonstrate the calculation procedure of the threshold. Finally, we present numerical simulations to demonstrate the usefulness of our proposed results.
Keywords:
Delay effects
Estimation
Kalman filters
Time measurement
Wireless sensor networks
Wireless communication
Intelligent sensors
State estimation
Remote state estimation
Kalman filter
networked systems
wireless sensor networks
time delay
Journal
I
IF:
7.9
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2.5K
Citations:
10.0K
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