Abstract
Radio-based localization has the potential to provide centimeter-level position information. In this paper we apply joint probabilistic data association to multipath-assisted simultaneous localization and mapping (SLAM) for this purpose. In multipath-assisted localization, position-related information in multipath components (MPCs) is exploited to increase the accuracy and robustness of indoor tracking. Based on a recently introduced loopy belief propagation multipath-assisted localization scheme that performs probabilistic data association jointly with agent state estimation, we build a method for SLAM without using apriori known environment maps. The proposed method is highly accurate and robust in localizing a mobile agent while building up an environment feature map. It scales well in all relevant systems parameters and has a very low computational complexity.
Originalsprache | englisch |
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Titel | 2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017 |
Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers |
Seiten | 652-658 |
Seitenumfang | 7 |
ISBN (elektronisch) | 9781509015252 |
DOIs | |
Publikationsstatus | Veröffentlicht - 29 Juni 2017 |
Veranstaltung | 2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017 - Paris, Frankreich Dauer: 21 Mai 2017 → 25 Mai 2017 |
Konferenz
Konferenz | 2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017 |
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Land/Gebiet | Frankreich |
Ort | Paris |
Zeitraum | 21/05/17 → 25/05/17 |
ASJC Scopus subject areas
- Computernetzwerke und -kommunikation
- Hardware und Architektur