Multipath-Based SLAM with Cooperation and Map Fusion in MIMO Systems

Multipath-based simultaneous localization and map-ping (MP-SLAM) is a promising approach in wireless networks for obtaining position information of transmitters and receivers as well as information on the propagation environment. MP-SLAM models specular reflections of radio signals at flat surfaces as virtual anchors (VAs), the mirror images of base stations (BSs). Conventional methods for MP-SLAM consider a single mobile terminal (MT) which has to be localized. The availability of additional MTs paves the way for utilizing additional information in the scenario. Specifically enabling MTs to exchange information allows for data fusion over different observations of VAs, made by different MTs, and cooperative localization. Utilizing this additional information enables more robust mapping and higher localization accuracy.

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Published
2024-10-27
DOI
https://doi.org/10.1109/ieeeconf60004.2024.10942778
Citations
4
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.85
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article

Multipath-Based SLAM with Cooperation and Map Fusion in MIMO Systems

Erik Leitinger, Alexander Venus, Lukas Wielandner, Mingchao Liang et al.
4 citations
Modular Robots and Swarm Intelligence
0.85
article

Multipath-Based SLAM with Cooperation and Map Fusion in MIMO Systems

Erik Leitinger, Alexander Venus, Lukas Wielandner, Mingchao Liang, Klaus Witrisal, Florian Meyer
article en
4 citations

Abstract

Multipath-based simultaneous localization and map-ping (MP-SLAM) is a promising approach in wireless networks for obtaining position information of transmitters and receivers as well as information on the propagation environment. MP-SLAM models specular reflections of radio signals at flat surfaces as virtual anchors (VAs), the mirror images of base stations (BSs). Conventional methods for MP-SLAM consider a single mobile terminal (MT) which has to be localized. The availability of additional MTs paves the way for utilizing additional information in the scenario. Specifically enabling MTs to exchange information allows for data fusion over different observations of VAs, made by different MTs, and cooperative localization. Utilizing this additional information enables more robust mapping and higher localization accuracy.

University of California San Diego (US), Graz University of Technology (AT)
Partnerships for the goals
Openalex Percentile: Top 29%
Modular Robots and Swarm Intelligence
0.85
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Multipath-Based SLAM with Cooperation and Map Fusion in MIMO Systems — Erik Leitinger, Alexander Venus, et al. · (2024) | TGRS Research Map | TGRS