Distributed energy-efficient target tracking algorithm based on event-triggered strategy for sensor networks

The distributed estimation problem for wireless sensor networks with limited communication/sensing ranges and observability is studied. A novel sensor measuring activation scheme based on a fully distributed event-triggered strategy is proposed to make each node achieve a better trade-off between es...

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Bibliographic Details
Published in:IET control theory & applications Vol. 13; no. 10; pp. 1564 - 1570
Main Authors: Zhang, Ya, Zhang, Lingling, Du, Lishuang, Liu, Cheng-Lin, Chen, Yang-Yang
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 02.07.2019
Subjects:
activation scheme
available distance‐based
Brief Paper
collaboratively observable sensor
communication/sensing
distributed energy‐efficient target
distributed estimation problem
distributed Kalman filtering algorithm
energy saving
estimation errors
event‐triggered measuring strategy
fully distributed event‐triggered strategy
Kalman filters
minimum trace fusion principle
observability
predicted position
predicted synthetic performance index
ranges
target tracking
time‐triggered strategy
trade‐off between estimation error
wireless sensor networks
predicted synthetic performance index
wireless sensor networks
ranges
trade-off between estimation error
minimum trace fusion principle
available distance-based
energy saving
time-triggered strategy
estimation errors
communication/sensing
fully distributed event-triggered strategy
collaboratively observable sensor
predicted position
target tracking
distributed energy-efficient target
distributed estimation problem
activation scheme
Kalman filters
event-triggered measuring strategy
observability
distributed Kalman filtering algorithm
ISSN:1751-8644, 1751-8652
Online Access:Get full text
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Summary:The distributed estimation problem for wireless sensor networks with limited communication/sensing ranges and observability is studied. A novel sensor measuring activation scheme based on a fully distributed event-triggered strategy is proposed to make each node achieve a better trade-off between estimation error and energy saving. The strategy depends on both the predicted synthetic performance index and the predicted position of the target. A distributed Kalman filtering algorithm based on the minimum trace fusion principle is proposed. It is proved that comparing with the time-triggered strategy, the proposed event-triggered measuring strategy has better performance. Although the event-triggered measuring topology is time-varying and each sensor is not observable, it is proved that as long as there exists at least one collaboratively observable sensor in the available distance-based sensing network at each time instant, the estimation errors are bounded in mean square sense. Simulation examples are given to illustrate the validity of the algorithm.
ISSN:1751-8644
1751-8652
DOI:10.1049/iet-cta.2018.5470