Cooperative mmWave PHD-SLAM with Moving Scatterers
Paper in proceeding, 2022

Simultaneous localization and mapping (SLAM) using multipath at mmWave frequencies can provide accurate localization in the presence of static landmarks. When radio signals reflected from moving vehicle scatterers (VSs) are observed, the standard SLAM filters exhibit a degraded performance. To address this problem, we propose a probability hypothesis density (PHD)-based SLAM filter, where separate maps are maintained for VS and other types of landmarks. Through a combination of developed (i) local PHD-SLAM and (ii) global map fusion, we demonstrate that the proposed filter can handle the problem.

Author

Hyowon Kim

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Jaebok Lee

Hanyang University

Yu Ge

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Fan Jiang

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Sunwoo Kim

Hanyang University

Henk Wymeersch

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

2022 25th International Conference on Information Fusion, FUSION 2022


9781737749721 (ISBN)

25th International Conference on Information Fusion, FUSION 2022
Linkoping, Sweden,

5G cellular positioning for vehicular safety

VINNOVA (2019-03085), 2020-01-01 -- 2021-12-31.

Subject Categories

Computational Mathematics

Signal Processing

Computer Vision and Robotics (Autonomous Systems)

DOI

10.23919/FUSION49751.2022.9841389

More information

Latest update

1/3/2024 9