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A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
Chalmers University of Technology, Göteborg, Sweden.ORCID iD: 0000-0003-1747-2664
Tampere University, Tampere, Finland.ORCID iD: 0000-0002-9336-7703
Chalmers University of Technology, Göteborg, Sweden.ORCID iD: 0000-0002-0473-1471
Chalmers University of Technology, Göteborg, Sweden.ORCID iD: 0000-0003-0598-0178
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2022 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 40, no 7, p. 2179-2192Article in journal (Refereed) Published
Abstract [en]

Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the propagation channel. To solve the SLAM problem, existing approaches rely on sigma-point or particle-based approximations, leading to high computational complexity, precluding real-Time execution. We propose a novel low-complexity SLAM filter, based on the Poisson multi-Bernoulli mixture (PMBM) filter. It utilizes the extended Kalman (EK) first-order Taylor series based Gaussian approximation of the filtering distribution, and applies the track-oriented marginal multi-Bernoulli/Poisson (TOMB/P) algorithm to approximate the resulting PMBM as a Poisson multi-Bernoulli (PMB). The filter can account for different landmark types in radio SLAM and multiple data association hypotheses. Hence, it has an adjustable complexity/performance trade-off. Simulation results show that the developed SLAM filter can greatly reduce the computational cost, while it keeps the good performance of mapping and user state estimation. © 1983-2012 IEEE.

Place, publisher, year, edition, pages
Piscataway: IEEE, 2022. Vol. 40, no 7, p. 2179-2192
Keywords [en]
Bistatic sensing, extended Kalman filter, mmWave sensing, poisson multi-Bernoulli mixture filter, simultaneous localization and mapping
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hh:diva-49158DOI: 10.1109/jsac.2022.3155504ISI: 000812531300016Scopus ID: 2-s2.0-85125707019OAI: oai:DiVA.org:hh-49158DiVA, id: diva2:1725147
Funder
Knut and Alice Wallenberg FoundationVinnova, 2019-03085Swedish Research Council, 2018-03705Academy of Finland, 315858Academy of Finland, 328214Academy of Finland, 319994Academy of Finland, 323244Academy of Finland, 346622Available from: 2023-01-10 Created: 2023-01-10 Last updated: 2023-02-15Bibliographically approved

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Jiang, Fan

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Ge, YuKaltiokallio, OssiKim, HyowonJiang, FanTalvitie, JukkaValkama, MikkoSvensson, LennartKim, SunwooWymeersch, Henk
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IEEE Journal on Selected Areas in Communications
Electrical Engineering, Electronic Engineering, Information Engineering

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