Simultaneous Localization of a Receiver and Mapping of Multipath Generating Geometry in Indoor Environments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00331671" target="_blank" >RIV/68407700:21230/18:00331671 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.ion.org/publications/abstract.cfm?articleID=16043" target="_blank" >https://www.ion.org/publications/abstract.cfm?articleID=16043</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.33012/2018.16043" target="_blank" >10.33012/2018.16043</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Simultaneous Localization of a Receiver and Mapping of Multipath Generating Geometry in Indoor Environments

Popis výsledku v původním jazyce

This paper presents a novel algorithm that aims at combining the pre-existing and dominating applications of radio signals, namely communication, navigation and sensing of an environment into an integrated approach. Practical applications of this algorithm include navigation in GNSS-denied environments and include the generation of geometric representations of surroundings based on signals implemented in current and future mobile cellular radio communication systems. We show that the power and spectral properties of such signals allow us, in addition to estimating the position of a receiver. Especially in indoor or urban scenarios, the signal reaching the receive antenna consists of multiple paths, called multipath. Multipath reception degrades the accuracy of the positioning device as long as the receiver is based on standard methods. With Channel-SLAM we introduced a novel algorithm which uses multipath components for positioning instead of mitigating them. Channel-SLAM treats each multipath component as a line-of-sight signal from a virtual transmitter which position is unknown to the receiver. Channel-SLAM basically uses a two level approach: The first level uses a Space-Alternating Generalized Expectation-Maximization (SAGE) based Kalman filter to estimate and track the amplitude and the delay of each multipath component. Afterwards, the second level estimates simultaneously the positions of the receiver and the virtual transmitters based on the estimated parameters of the multipath components using a simultaneous localization and mapping (SLAM) approach. In this paper, we extend Channel-SLAM to exploit the geometry information of the surrounding area. Furthermore, mapping the geometry layout helps to improve the position estimation. To verify the proposed algorithm, we evaluate the algorithm based on measurements using an ultra-wideband (UWB) system.

Název v anglickém jazyce

Simultaneous Localization of a Receiver and Mapping of Multipath Generating Geometry in Indoor Environments

Popis výsledku anglicky

This paper presents a novel algorithm that aims at combining the pre-existing and dominating applications of radio signals, namely communication, navigation and sensing of an environment into an integrated approach. Practical applications of this algorithm include navigation in GNSS-denied environments and include the generation of geometric representations of surroundings based on signals implemented in current and future mobile cellular radio communication systems. We show that the power and spectral properties of such signals allow us, in addition to estimating the position of a receiver. Especially in indoor or urban scenarios, the signal reaching the receive antenna consists of multiple paths, called multipath. Multipath reception degrades the accuracy of the positioning device as long as the receiver is based on standard methods. With Channel-SLAM we introduced a novel algorithm which uses multipath components for positioning instead of mitigating them. Channel-SLAM treats each multipath component as a line-of-sight signal from a virtual transmitter which position is unknown to the receiver. Channel-SLAM basically uses a two level approach: The first level uses a Space-Alternating Generalized Expectation-Maximization (SAGE) based Kalman filter to estimate and track the amplitude and the delay of each multipath component. Afterwards, the second level estimates simultaneously the positions of the receiver and the virtual transmitters based on the estimated parameters of the multipath components using a simultaneous localization and mapping (SLAM) approach. In this paper, we extend Channel-SLAM to exploit the geometry information of the surrounding area. Furthermore, mapping the geometry layout helps to improve the position estimation. To verify the proposed algorithm, we evaluate the algorithm based on measurements using an ultra-wideband (UWB) system.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018)

ISBN

9780936406107

ISSN

—

e-ISSN

—

Počet stran výsledku

18

Strana od-do

635-652

Název nakladatele

The Institute of Navigation (ION)

Místo vydání

Manassas, VA

Místo konání akce

Miami, Florida

Datum konání akce

24. 9. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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