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Distributed Bayesian target tracking with reduced communication: Likelihood consensus 2.0

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU149052" target="_blank" >RIV/00216305:26220/24:PU149052 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S016516842300333X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S016516842300333X</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.sigpro.2023.109259" target="_blank" >10.1016/j.sigpro.2023.109259</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Distributed Bayesian target tracking with reduced communication: Likelihood consensus 2.0

  • Original language description

    The likelihood consensus (LC) enables Bayesian target tracking in a decentralized sensor network with possibly nonlinear and non-Gaussian sensor characteristics. Here, we propose an evolved LC methodology—dubbed “LC 2.0”—with significantly reduced intersensor communication. LC 2.0 uses multiple refinements of the original LC including a sparsity-promoting calculation of expansion coefficients, the use of a B-spline dictionary, a distributed adaptive calculation of the relevant state-space region, and efficient binary representations. We consider the use of the proposed LC 2.0 within a distributed particle filter and within a distributed particle-based probabilistic data association filter. Our simulation results demonstrate that a reduction of intersensor communication by a factor of about 190 can be obtained without compromising the tracking performance.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20202 - Communication engineering and systems

Result continuities

  • Project

    <a href="/en/project/8J19AT029" target="_blank" >8J19AT029: Advanced Bayesian Tracking Methods for Medical Imaging and Mobile Communications</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    SIGNAL PROCESSING

  • ISSN

    0165-1684

  • e-ISSN

    1879-2677

  • Volume of the periodical

    215

  • Issue of the periodical within the volume

    February 2024

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    13

  • Pages from-to

    1-13

  • UT code for WoS article

    001101697800001

  • EID of the result in the Scopus database

    2-s2.0-85174005243