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Algorithm for Positioning in Non-line-of-Sight Conditions Using Unmanned Aerial Vehicles

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2018, ruSMART 2018)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11118))

Abstract

The identification of Line of Sight (LOS) in the processing of navigational measurements is relevant for positioning in urban conditions, as well as in heterogeneous terrain such as mountains and hills, when there is no direct visibility between the radio source and the receiving stations. The purpose of this work is to develop and verify algorithm for positioning a transmitting radio source in Non-Line-of-Sight Conditions (NLOS) using Unmanned Aerial Vehicles (UAVs) in three dimensional space. Algorithm under consideration implements time difference of arrival (TDOA) measurements processing for identification of receivers with NLOS measurements. Algorithm operability is illustrated for the layout including terrestrial segment with ground receiver stations and flying segment with receiving sensors aboard UAVs. The method used for NLOS identification and mitigation exploits the comparison of variance for intermediate location estimates calculated for different TDOA measurements combinations among all possible sets of receivers with thresholds. Algorithm was realized in simulation model including system level, link level and visualization model subsystems. TDOA system level model represents positioning layout with distributed transmitter, receivers, obstacles and NLOS reflectors in three dimensional space. TDOA link level model represents radio links between transmitter, receivers, and NLOS reflectors taking into account actual pathloss, signal modulation, sampling rate, additive noise and cross-correlation calculation. Comparing with the case on the plane, TDOA measurements processing in three dimensional space case with flying receiver aboard UAVs reveals substantially higher thresholds of calculated variances to reliably identify and exclude NLOS source.

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Acknowledgements

The reported study was supported by the Committee on Science and Higher School of the Government of St. Petersburg.

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Authors and Affiliations

  1. The Bonch-Bruevich St. Petersburg State University of Telecommunications, St. Petersburg, Russia

    Grigoriy Fokin & Al-odhari Abdulwahab Hussain Ali

Authors
  1. Grigoriy Fokin
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  2. Al-odhari Abdulwahab Hussain Ali
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Correspondence to Grigoriy Fokin .

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Editors and Affiliations

  1. Tampere University of Technology, Tampere, Finland

    Olga Galinina

  2. Tampere University of Technology, Tampere, Finland

    Sergey Andreev

  3. FRUCT Oy, Helsinki, Finland

    Sergey Balandin

  4. Tampere University of Technology, Tampere, Finland

    Yevgeni Koucheryavy

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Fokin, G., Ali, Ao.A.H. (2018). Algorithm for Positioning in Non-line-of-Sight Conditions Using Unmanned Aerial Vehicles. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2018 2018. Lecture Notes in Computer Science(), vol 11118. Springer, Cham. https://doi.org/10.1007/978-3-030-01168-0_44

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  • DOI: https://doi.org/10.1007/978-3-030-01168-0_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01167-3

  • Online ISBN: 978-3-030-01168-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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