On hybrid consensus-based extended Kalman filtering with random link failures over sensor networks

Pailiang Zhu; Guoliang Wei; Jiajia Li

Kybernetika (2020)

  • Volume: 56, Issue: 1, page 189-212
  • ISSN: 0023-5954

Abstract

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This paper is concerned with the distributed filtering problem for nonlinear time-varying systems over wireless sensor networks under random link failures. To achieve consensus estimation, each sensor node is allowed to communicate with its neighboring nodes according to a prescribed communication topology. Firstly, a new hybrid consensus-based filtering algorithm under random link failures, which affect the information exchange between sensors and are modeled by a set of independent Bernoulli processes, is designed via redefining the interaction weights. Second, a novel observability condition, called parameterized jointly uniform observability, is proposed to ensure the stochastic boundedness of the error covariances of the hybrid consensus-based filtering algorithm. Finally, an example is given to demonstrate the effectiveness of the derived theoretical results.

How to cite

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Zhu, Pailiang, Wei, Guoliang, and Li, Jiajia. "On hybrid consensus-based extended Kalman filtering with random link failures over sensor networks." Kybernetika 56.1 (2020): 189-212. <http://eudml.org/doc/297181>.

@article{Zhu2020,
abstract = {This paper is concerned with the distributed filtering problem for nonlinear time-varying systems over wireless sensor networks under random link failures. To achieve consensus estimation, each sensor node is allowed to communicate with its neighboring nodes according to a prescribed communication topology. Firstly, a new hybrid consensus-based filtering algorithm under random link failures, which affect the information exchange between sensors and are modeled by a set of independent Bernoulli processes, is designed via redefining the interaction weights. Second, a novel observability condition, called parameterized jointly uniform observability, is proposed to ensure the stochastic boundedness of the error covariances of the hybrid consensus-based filtering algorithm. Finally, an example is given to demonstrate the effectiveness of the derived theoretical results.},
author = {Zhu, Pailiang, Wei, Guoliang, Li, Jiajia},
journal = {Kybernetika},
keywords = {extended Kalman filter; hybrid consensus filter; sensor network; distributed state estimation; random link failure},
language = {eng},
number = {1},
pages = {189-212},
publisher = {Institute of Information Theory and Automation AS CR},
title = {On hybrid consensus-based extended Kalman filtering with random link failures over sensor networks},
url = {http://eudml.org/doc/297181},
volume = {56},
year = {2020},
}

TY - JOUR
AU - Zhu, Pailiang
AU - Wei, Guoliang
AU - Li, Jiajia
TI - On hybrid consensus-based extended Kalman filtering with random link failures over sensor networks
JO - Kybernetika
PY - 2020
PB - Institute of Information Theory and Automation AS CR
VL - 56
IS - 1
SP - 189
EP - 212
AB - This paper is concerned with the distributed filtering problem for nonlinear time-varying systems over wireless sensor networks under random link failures. To achieve consensus estimation, each sensor node is allowed to communicate with its neighboring nodes according to a prescribed communication topology. Firstly, a new hybrid consensus-based filtering algorithm under random link failures, which affect the information exchange between sensors and are modeled by a set of independent Bernoulli processes, is designed via redefining the interaction weights. Second, a novel observability condition, called parameterized jointly uniform observability, is proposed to ensure the stochastic boundedness of the error covariances of the hybrid consensus-based filtering algorithm. Finally, an example is given to demonstrate the effectiveness of the derived theoretical results.
LA - eng
KW - extended Kalman filter; hybrid consensus filter; sensor network; distributed state estimation; random link failure
UR - http://eudml.org/doc/297181
ER -

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