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Abstract
Multipath-based simultaneous localization and map-
ping (SLAM) is a promising approach to obtain position in-
formation of transmitters and receivers as well as information
regarding the propagation environments in future mobile com-
munication systems. Usually, specular reflections of the radio
signals occurring at flat surfaces are modeled by virtual anchors
(VAs) that are mirror images of the physical anchors (PAs). In
existing methods for multipath-based SLAM, each VA is assumed
to generate only a single measurement. However, due to imper-
fections of the measurement equipment such as non-calibrated
antennas or model mismatch due to roughness of the reflective
surfaces, there are potentially multiple multipath components
(MPCs) that are associated to one single VA. In this paper,
we introduce a Bayesian particle-based sum-product algorithm
(SPA) for multipath-based SLAM that can cope with multiple-
measurements being associated to a single VA. Furthermore, we
introduce a novel statistical measurement model that is strongly
related to the radio signal. It introduces additional dispersion
parameters into the likelihood function to capture additional
MPCs-related measurements. We demonstrate that the proposed
SLAM method can robustly fuse multiple measurements per VA
based on numerical simulations.
ping (SLAM) is a promising approach to obtain position in-
formation of transmitters and receivers as well as information
regarding the propagation environments in future mobile com-
munication systems. Usually, specular reflections of the radio
signals occurring at flat surfaces are modeled by virtual anchors
(VAs) that are mirror images of the physical anchors (PAs). In
existing methods for multipath-based SLAM, each VA is assumed
to generate only a single measurement. However, due to imper-
fections of the measurement equipment such as non-calibrated
antennas or model mismatch due to roughness of the reflective
surfaces, there are potentially multiple multipath components
(MPCs) that are associated to one single VA. In this paper,
we introduce a Bayesian particle-based sum-product algorithm
(SPA) for multipath-based SLAM that can cope with multiple-
measurements being associated to a single VA. Furthermore, we
introduce a novel statistical measurement model that is strongly
related to the radio signal. It introduces additional dispersion
parameters into the likelihood function to capture additional
MPCs-related measurements. We demonstrate that the proposed
SLAM method can robustly fuse multiple measurements per VA
based on numerical simulations.
| Originalsprache | englisch |
|---|---|
| Seiten (von - bis) | 59-77 |
| Fachzeitschrift | Journal of Advances in Information Fusion |
| Jahrgang | 18 |
| Ausgabenummer | 2 |
| Publikationsstatus | Veröffentlicht - 11 Sept. 2023 |
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CD-Labor für Ortssensitive Elektronische Systeme
Witrisal, K. (Teilnehmer (Co-Investigator)), Grebien, S. J. (Teilnehmer (Co-Investigator)), Fuchs, A. (Teilnehmer (Co-Investigator)), Wilding, T. (Teilnehmer (Co-Investigator)), Venus, A. (Teilnehmer (Co-Investigator)) & Wielandner, L. (Teilnehmer (Co-Investigator))
1/01/18 → 31/12/25
Projekt: Forschungsprojekt