Y
Yu Ge
Researcher at Chalmers University of Technology
Publications - 9
Citations - 102
Yu Ge is an academic researcher from Chalmers University of Technology. The author has contributed to research in topics: Simultaneous localization and mapping & Multipath propagation. The author has an hindex of 3, co-authored 9 publications receiving 26 citations. Previous affiliations of Yu Ge include Hanyang University.
Papers
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Journal ArticleDOI
5G SLAM Using the Clustering and Assignment Approach with Diffuse Multipath
TL;DR: This study considers an intermediate approach, which consists of four phases—downlink data transmission, multi-dimensional channel estimation, channel parameter clustering, and simultaneous localization and mapping (SLAM) based on a novel likelihood function.
Proceedings ArticleDOI
High-dimensional Channel Estimation for Simultaneous Localization and Communications
TL;DR: In this paper, a low-complexity multidimensional channel parameter estimation via rotational invariance techniques (MD-ESPRIT) is proposed for simultaneous positioning and mapping.
Proceedings ArticleDOI
Exploiting Diffuse Multipath in 5G SLAM
TL;DR: In this article, a Poisson multi-Bernoulli mixture for the 5G SLAM problem is proposed, which incorporates all available multipath signals from each landmark for mapping and incorporates this into a poisson multinomial mixture.
Posted Content
Exploiting Diffuse Multipath in 5G SLAM
TL;DR: A novel method to utilize all available multipath signals from each landmark for mapping and incorporate this into a Poisson multi-Bernoulli mixture for the 5G SLAM problem is proposed.
Posted Content
A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
Yu Ge,Ossi Kaltiokallio,Hyowon Kim,Fan Jiang,Jukka Talvitie,Mikko Valkama,Lennart Svensson,Sunwoo Kim,Henk Wymeersch +8 more
TL;DR: In this article, the authors proposed a low-complexity SLAM filter based on the Poisson multi-Bernoulli mixture (PMBM) filter, which utilizes the extended Kalman (EK) first-order Taylor series based Gaussian approximation of the filtering distribution.