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

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

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

  • ISBN

    9780936406107

  • ISSN

  • e-ISSN

  • Number of pages

    18

  • Pages from-to

    635-652

  • Publisher name

    The Institute of Navigation (ION)

  • Place of publication

    Manassas, VA

  • Event location

    Miami, Florida

  • Event date

    Sep 24, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article