Cooperative mmWave PHD-SLAM with Moving Scatterers
Paper i 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.

Författare

Hyowon Kim

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Jaebok Lee

Hanyang University

Yu Ge

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Fan Jiang

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Sunwoo Kim

Hanyang University

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

2022 25th International Conference on Information Fusion, FUSION 2022


9781737749721 (ISBN)

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

5G mobil positionering för fordonssäkerhet

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

Ämneskategorier

Beräkningsmatematik

Signalbehandling

Datorseende och robotik (autonoma system)

DOI

10.23919/FUSION49751.2022.9841389

Mer information

Senast uppdaterat

2024-01-03