ICASSP 2020accepted0 citations
Low-Complexity 5g Slam with CKF-PHD Filter
Hyowon Kim, Karl Granström, Sunwoo Kim, Henk Wymeersch
Abstract
In 5G mmWave, simultaneous localization and mapping (SLAM) allows devices to exploit map information to improve their position estimate. Even the most basic SLAM filter based on a Rao-Blackwellized particle filter (RBPF) combined with a probability hypothesis density (PHD) map representation exhibits high complexity. This paper proposes a new implementation method for the 5G SLAM using message passing (MP) and the cubature Kalman filter (CKF). We demonstrate that the proposed method significantly reduces the complexity while retaining the SLAM accuracy of the RBPF-PHD approach.
BibTeX
@inproceedings{icassp2020_lowcomplexity5gs,
title = {Low-Complexity 5g Slam with CKF-PHD Filter},
author = {Hyowon Kim and Karl Granström and Sunwoo Kim and Henk Wymeersch},
booktitle = {ICASSP 2020},
year = {2020}
}