A Belief Propagation Algorithm for Multipath-Based SLAM
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU140250" target="_blank" >RIV/00216305:26220/19:PU140250 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8823946" target="_blank" >https://ieeexplore.ieee.org/document/8823946</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TWC.2019.2937781" target="_blank" >10.1109/TWC.2019.2937781</a>
Alternative languages
Result language
angličtina
Original language name
A Belief Propagation Algorithm for Multipath-Based SLAM
Original language description
We present a simultaneous localization and mapping (SLAM) algorithm that is based on radio signals and the association of specular multipath components (MPCs) with geometric features. Especially in indoor scenarios, robust localization from radio signals is challenging due to diffuse multipath propagation, unknown MPC-feature association, and limited visibility of features. In our approach, specular reflections at flat surfaces are described in terms of virtual anchors (VAs) that are mirror images of the physical anchors (PAs). The positions of these VAs and possibly also of the PAs are unknown. We develop a Bayesian model of the SLAM problem and represent it by a factor graph, which enables the use of belief propagation (BP) for efficient marginalization of the joint posterior distribution. The resulting BP-based SLAM algorithm detects the VAs associated with the PAs and estimates jointly the time-varying position of the mobile agent and the positions of the VAs and possibly also of the PAs, thereby leveraging the MPCs in the radio signal for improved accuracy and robustness of agent localization. The algorithm has a low computational complexity and scales well in all relevant system parameters. Experimental results using both synthetic measurements and real ultra-wideband radio signals demonstrate the excellent performance of the algorithm in challenging indoor environments.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/GA17-19638S" target="_blank" >GA17-19638S: Sequential Bayesian Estimation of Arterial Wall Motion</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
ISSN
1536-1276
e-ISSN
1558-2248
Volume of the periodical
18
Issue of the periodical within the volume
12
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
5613-5629
UT code for WoS article
000510852500011
EID of the result in the Scopus database
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