Fast Kalman filter synchronization algorithm for cooperative synchronization in time sensitive networks

Ji, Ruoyu; Xu, Fangmin; Tao, Yiwen; Feng, Tao; Zhao, Chenglin

doi:10.1016/j.dsp.2023.104255

Digital Signal Processing

2023

DOI: 10.1016/j.dsp.2023.104255

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Fast Kalman filter synchronization algorithm for cooperative synchronization in time sensitive networks

Ruoyu Ji,

Fangmin Xu,

Yiwen Tao

et al.

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2024

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Exploiting sparsity for localisation of large‐scale wireless sensor networks

Khan,

Hwang,

Goppert

2024

IET Wireless Sensor Systems

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Wireless Sensor Network (WSN) localisation refers to the problem of determining the position of each of the agents in a WSN using noisy measurement information. In many cases, such as in distance and bearing‐based localisation, the measurement model is a non‐linear function of the agents' positions, leading to pairwise interconnections between the agents. As the optimal solution for the WSN localisation problem is known to be computationally expensive in these cases, an efficient approximation is desired. The authors show that the inherent sparsity in this problem can be exploited to greatly reduce the computational effort of using an Extended Kalman Filter (EKF) for large‐scale WSN localisation. In the proposed method, which the authors call the L‐Banded Extended Kalman Filter (LB‐EKF), the measurement information matrix is converted into a banded matrix by relabelling (permuting the order of) the vertices of the graph. Using a combination of theoretical analysis and numerical simulations, it is shown that typical WSN configurations (which can be modelled as random geometric graphs) can be localised in a scalable manner using the proposed LB‐EKF approach.

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Exploiting sparsity for localisation of large‐scale wireless sensor networks

Khan,

Hwang,

Goppert

2024

IET Wireless Sensor Systems

View full text Add to dashboard Cite

show abstract

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Fast Kalman filter synchronization algorithm for cooperative synchronization in time sensitive networks

Cited by 1 publication

References 24 publications

Exploiting sparsity for localisation of large‐scale wireless sensor networks

Exploiting sparsity for localisation of large‐scale wireless sensor networks

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