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Abstract
Precise indoor localization remains a challenging problem for a variety of essential applications. A promising approach to address this problem is to exchange radio signals between mobile agents and static physical anchors (PAs) that bounce off flat surfaces in the indoor environment. Radio frequency simultaneous localization and mapping (RF -SLAM) methods can be used to jointly estimates the time-varying location of agents as well as the static locations of the flat surfaces. Recent work on RF -SLAM methods has shown that each surface can be efficiently represented by a single master virtual anchor (MVA). The measurement model related to this MVA-based RF -SLAM method is highly nonlinear. Thus, Bayesian estimation relies on sampling-based techniques. The original MVA-based RF -SLAM method employs conventional 'bootstrap' sampling. In challenging scenarios it was observed that the original method might converge to incorrect MVA positions corresponding to local maxima. In this paper, we introduce MVA-based RF-SLAM with an improved sampling technique that succeeds in the aforementioned challenging scenarios. Our simulation results demonstrate significant performance advantages.
Original language | English |
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Title of host publication | 2022 25th International Conference on Information Fusion, FUSION 2022 |
Place of Publication | Linköping, Sweden |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 9781737749721 |
DOIs | |
Publication status | Published - 1 Jul 2022 |
Event | 25th International Conference on Information Fusion: FUSION 2022 - Linkoping, Sweden Duration: 4 Jul 2022 → 7 Jul 2022 |
Conference
Conference | 25th International Conference on Information Fusion |
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Country/Territory | Sweden |
City | Linkoping |
Period | 4/07/22 → 7/07/22 |
ASJC Scopus subject areas
- Information Systems and Management
- Information Systems
- Signal Processing
- Computer Vision and Pattern Recognition
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Dive into the research topics of 'Data Fusion for Radio Frequency SLAM with Robust Sampling'. Together they form a unique fingerprint.Projects
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CD-Laboratory for Location-aware Electronic Systems
Witrisal, K., Grebien, S. J., Fuchs, A., Wilding, T., Venus, A. & Wielandner, L.
1/01/18 → 31/12/24
Project: Research project