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Detail publikačního výsledku
ŠAUŠA, E.; RAJMIC, P.; HLAWATSCH, F.
Originální název
Likelihood Consensus 2.0: Reducing Interagent Communication in Distributed Bayesian Target Tracking
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
We propose a communication-efficient scheme for distributed Bayesian target tracking (distributed particle filtering) in possibly nonlinear and non-Gaussian state-space models. The scheme is a sparsity-promoting evolution of the likelihood consensus (LC) that uses the orthogonal matching pursuit (OMP), a B-spline dictionary, a distributed adaptive determination of the relevant state-space region, and an efficient binary representation of the LC expansion coefficients. Our simulation results show that a reduction of interagent communication by a factor of about 190 can be obtained without compromising the tracking performance.
Anglický abstrakt
Klíčová slova
Target tracking; distributed particle filter; Bayesian filtering; likelihood consensus; sparsity
Klíčová slova v angličtině
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Rok RIV
2025
Vydáno
14.04.2024
Nakladatel
IEEE
Místo
Soul
ISBN
979-8-3503-4485-1
Kniha
49th IEEE International Conference on Acoustics, Speech, and Signal Processing
Strany počet
5
BibTex
@inproceedings{BUT197325, author="Erik {Šauša} and Pavel {Rajmic} and Franz {Hlawatsch}", title="Likelihood Consensus 2.0: Reducing Interagent Communication in Distributed Bayesian Target Tracking", booktitle="49th IEEE International Conference on Acoustics, Speech, and Signal Processing", year="2024", pages="5", publisher="IEEE", address="Soul", doi="10.1109/ICASSP48485.2024.10447108", isbn="979-8-3503-4485-1" }