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

  • Grigoriy FokinEmail author
  • Al-odhari Abdulwahab Hussain Ali
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

TDOA NLOS UAV Root mean square error Measurement processing 

Notes

Acknowledgements

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

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Grigoriy Fokin
    • 1
    Email author
  • Al-odhari Abdulwahab Hussain Ali
    • 1
  1. 1.The Bonch-Bruevich St. Petersburg State University of TelecommunicationsSt. PetersburgRussia

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