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Distributed algorithms for tracking the trajectories of many objects by the set of mobile sensors. / Ivanskiy, Yury; Sergeenko, Anna.

в: IOP Conference Series: Materials Science and Engineering, Том 984, № 1, 012003, 2020.

Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование

Harvard

Ivanskiy, Y & Sergeenko, A 2020, 'Distributed algorithms for tracking the trajectories of many objects by the set of mobile sensors', IOP Conference Series: Materials Science and Engineering, Том. 984, № 1, 012003. https://doi.org/10.1088/1757-899X/984/1/012003

APA

Ivanskiy, Y., & Sergeenko, A. (2020). Distributed algorithms for tracking the trajectories of many objects by the set of mobile sensors. IOP Conference Series: Materials Science and Engineering, 984(1), [012003]. https://doi.org/10.1088/1757-899X/984/1/012003

Vancouver

Ivanskiy Y, Sergeenko A. Distributed algorithms for tracking the trajectories of many objects by the set of mobile sensors. IOP Conference Series: Materials Science and Engineering. 2020;984(1). 012003. https://doi.org/10.1088/1757-899X/984/1/012003

Author

Ivanskiy, Yury ; Sergeenko, Anna. / Distributed algorithms for tracking the trajectories of many objects by the set of mobile sensors. в: IOP Conference Series: Materials Science and Engineering. 2020 ; Том 984, № 1.

BibTeX

@article{aae9e7a746d64fb48020fac245558795,
title = "Distributed algorithms for tracking the trajectories of many objects by the set of mobile sensors",
abstract = "We consider a dynamic network system of multiple heterogeneous sensors collaborating among themselves to estimate an unknown signal of interest. That communication capability is essential because individual senors cannot fulfill the task due to the lack of necessary information. This paper considers the distributed estimation or tracking problem and focuses on combining two algorithms: Simultaneous Perturbation Stochastic Approximation (SPSA) and consensus Local Voting Protocol (LVP). The new distributed algorithm is proposed for network systems under wide range of uncertainties including unknown-but-bounded drift of parameters and noise in observations. The suggested approach is illustrated by an application of the proposed algorithm to the solving the multisensor-multitarget problem.",
author = "Yury Ivanskiy and Anna Sergeenko",
note = "Funding Information: The theoretical part Sections I-V of this work was supported SPbSU by Russian Science Foundation (project no. 19-71-10012). The obtaining of experimental results in Section VI was supported by the Russian Fund for Basic Research (project no. 20-01-00619). Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2020 International Workshop on Navigation and Motion Control, NMC 2020 ; Conference date: 28-09-2020 Through 04-10-2020",
year = "2020",
doi = "10.1088/1757-899X/984/1/012003",
language = "English",
volume = "984",
journal = "IOP Conference Series: Materials Science and Engineering",
issn = "1757-8981",
publisher = "IOP Publishing Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Distributed algorithms for tracking the trajectories of many objects by the set of mobile sensors

AU - Ivanskiy, Yury

AU - Sergeenko, Anna

N1 - Funding Information: The theoretical part Sections I-V of this work was supported SPbSU by Russian Science Foundation (project no. 19-71-10012). The obtaining of experimental results in Section VI was supported by the Russian Fund for Basic Research (project no. 20-01-00619). Publisher Copyright: © Published under licence by IOP Publishing Ltd. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - We consider a dynamic network system of multiple heterogeneous sensors collaborating among themselves to estimate an unknown signal of interest. That communication capability is essential because individual senors cannot fulfill the task due to the lack of necessary information. This paper considers the distributed estimation or tracking problem and focuses on combining two algorithms: Simultaneous Perturbation Stochastic Approximation (SPSA) and consensus Local Voting Protocol (LVP). The new distributed algorithm is proposed for network systems under wide range of uncertainties including unknown-but-bounded drift of parameters and noise in observations. The suggested approach is illustrated by an application of the proposed algorithm to the solving the multisensor-multitarget problem.

AB - We consider a dynamic network system of multiple heterogeneous sensors collaborating among themselves to estimate an unknown signal of interest. That communication capability is essential because individual senors cannot fulfill the task due to the lack of necessary information. This paper considers the distributed estimation or tracking problem and focuses on combining two algorithms: Simultaneous Perturbation Stochastic Approximation (SPSA) and consensus Local Voting Protocol (LVP). The new distributed algorithm is proposed for network systems under wide range of uncertainties including unknown-but-bounded drift of parameters and noise in observations. The suggested approach is illustrated by an application of the proposed algorithm to the solving the multisensor-multitarget problem.

UR - http://www.scopus.com/inward/record.url?scp=85097678651&partnerID=8YFLogxK

U2 - 10.1088/1757-899X/984/1/012003

DO - 10.1088/1757-899X/984/1/012003

M3 - Conference article

AN - SCOPUS:85097678651

VL - 984

JO - IOP Conference Series: Materials Science and Engineering

JF - IOP Conference Series: Materials Science and Engineering

SN - 1757-8981

IS - 1

M1 - 012003

T2 - 2020 International Workshop on Navigation and Motion Control, NMC 2020

Y2 - 28 September 2020 through 4 October 2020

ER -

ID: 72795201