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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Vydáno v:	IET control theory & applications Ročník 13; číslo 10; s. 1564 - 1570
Hlavní autoři:	Zhang, Ya, Zhang, Lingling, Du, Lishuang, Liu, Cheng-Lin, Chen, Yang-Yang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 02.07.2019
Témata:	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
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Shrnutí:	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