Joint CKF-PHD Filter and Map Fusion for 5G Multi-cell SLAM
Paper i proceeding, 2020

5G is expected to enable simultaneous vehicle localization and environment mapping (SLAM). Furthermore, vehicular networks will be covered with 5G small cells, wherein the map information is collected at each base station (BS) and then fused so as to promote the overall performance of SLAM. In 5G multi-cell SLAM, there are challenges such as the unknown number of targets, uncertainty regarding the association between the targets and the measurements, unknown types of targets, as well as map management among BSs. To address those challenges, we propose a new method for 5G multi-cell SLAM which comprises a joint cubature Kalman filter and multi-model probability hypothesis density, and a map fusion routine. Simulation results demonstrate that the proposed method solves the aforementioned challenges and also improves vehicle state and map estimates.

5G multi-cell SLAM

joint CKF

map fusion

message passing

PHD

Författare

Hyowon Kim

Hanyang University

Karl Granström

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Lin Gao

Universita degli Studi di Firenze

Giorgio Battistelli

Universita degli Studi di Firenze

Sunwoo Kim

Hanyang University

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

IEEE International Conference on Communications

15503607 (ISSN)

Vol. 2020-June 9149211

2020 IEEE International Conference on Communications, ICC 2020
Dublin, Ireland,

Flerdimensionell koherentkommunikation med mikrofrekvenskammar

Vetenskapsrådet (VR), 2020-12-01 -- 2026-11-30.

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Kommunikationssystem

Annan medicinsk bioteknologi

Robotteknik och automation

DOI

10.1109/ICC40277.2020.9149211

Mer information

Senast uppdaterat

2021-03-08