Iterated Posterior Linearization PMB Filter for 5G SLAM
Paper i proceeding, 2022

5G millimeter wave (mmWave) signals have inherent geometric connections to the propagation channel and the propagation environment. Thus, they can be used to jointly localize the receiver and map the propagation environment, which is termed as simultaneous localization and mapping (SLAM). One of the most important tasks in the 5G SLAM is to deal with the nonlinearity of the measurement model. To solve this problem, existing 5G SLAM approaches rely on sigma-point or extended Kalman filters, linearizing the measurement function with respect to the prior probability density function (PDF). In this paper, we study the linearization of the measurement function with respect to the posterior PDF, and implement the iterated posterior linearization filter into the Poisson multi-Bernoulli SLAM filter. Simulation results demonstrate the accuracy and precision improvements of the resulting SLAM filter.

5G

Poisson multi-Bernoulli filter

posterior linearization

SLAM

mmWave

Författare

Yu Ge

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Yibo Wu

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Fan Jiang

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Ossi Kaltiokallio

Tampereen Yliopisto

Jukka Talvitie

Tampereen Yliopisto

M. Valkama

Tampereen Yliopisto

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

IEEE International Conference on Communications

15503607 (ISSN)

Vol. 2022-May 877-882
9781538683477 (ISBN)

2022 IEEE International Conference on Communications, ICC 2022
Seoul, South Korea,

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Ämneskategorier

Beräkningsmatematik

Reglerteknik

Signalbehandling

DOI

10.1109/ICC45855.2022.9839281

Mer information

Senast uppdaterat

2024-10-18