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)


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.


TDOA NLOS UAV Root mean square error Measurement processing 



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


  1. 1.
    Gelgor, A., Pavlenko, I., Fokin, G., Gorlov, A., Popov, E., Lavrukhin, V.: LTE base stations localization. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) NEW2AN 2014. LNCS, vol. 8638, pp. 191–204. Springer, Cham (2014). Scholar
  2. 2.
    Sivers, M., Fokin, G.: LTE positioning accuracy performance evaluation. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) ruSMART 2015. LNCS, vol. 9247, pp. 393–406. Springer, Cham (2015). Scholar
  3. 3.
    Fokin, G., Kireev, A., Al-odhari, A.H.A.: TDOA positioning accuracy performance evaluation for arc sensor configuration. In: 2018 Systems of Signals Generating and Processing in the Field of on Board Communications, Moscow, pp. 1–5 (2018)Google Scholar
  4. 4.
    Kireev, A., Fokin, G., Al-odhari, A.H.A.: TOA measurement processing analysis for positioning in NLOS conditions. In: 2018 Systems of Signals Generating and Processing in the Field of on Board Communications, Moscow, Russia, pp. 1–4 (2018)Google Scholar
  5. 5.
    Zekavat, R., Buehrer, R.M.: Handbook of Position Location: Theory, Practice and Advances. Wiley, Hoboken (2011)Google Scholar
  6. 6.
    Al-odhari, A.H.A., Fokin, G., Kireev, A.: Positioning of the radio source based on time difference of arrival method using unmanned aerial vehicles. In: 2018 Systems of Signals Generating and Processing in the Field of on Board Communications, Moscow, pp. 1–5 (2018)Google Scholar
  7. 7.
    Cong, L., Zhuang, W.: Nonline-of-sight error mitigation in mobile location. IEEE Trans. Wirel. Commun. 4(2), 560–573 (2005)CrossRefGoogle Scholar
  8. 8.
    Wylie, M.P., Holtzman, J.: The non-line of sight problem in mobile location estimation. In: Proceedings of ICUPC - 5th International Conference on Universal Personal Communications, Cambridge, MA, vol. 2, pp. 827–831 (1996)Google Scholar
  9. 9.
    Chen, P.C.: A non-line-of-sight error mitigation algorithm in location estimation. In: Proceedings of WCNC. IEEE Wireless Communications and Networking Conference (Cat. No. 99TH8466), New Orleans, LA, vol. 1, pp. 316–320 (1999)Google Scholar
  10. 10.
    Cong, L., Zhuang, W.: Non-line-of-sight error mitigation in TDOA mobile location. In: Proceedings of Global Telecommunications Conference. GLOBECOM 2001, vol. 1, pp. 680–684. IEEE, San Antonio (2001)Google Scholar
  11. 11.
    Montminy, M.B.: Passive geolocation of low-power emitters in urban environments using TDOA. Master’s thesis, Air Force Institute of Technology (2007)Google Scholar
  12. 12.
    3GPP TR 36.814 V9.2.0. Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Further advancements for E-UTRA physical layer aspects (2017)Google Scholar
  13. 13.
    Fokin, G.: Complex imitation model of radio emission sources positioning in the non-line-of-sight conditions. In: Proceedings of Telecommunication Universities, vol. 4(1), pp. 85–101 (2018)CrossRefGoogle Scholar
  14. 14.
    Koucheryavy, A., Vladyko, A., Kirichek, R.: State of the art and research challenges for public flying ubiquitous sensor networks. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) ruSMART 2015. LNCS, vol. 9247, pp. 299–308. Springer, Cham (2015). Scholar
  15. 15.
    Kirichek, R., Paramonov, A., Vareldzhyan, K.: Optimization of the UAV-P’s motion trajectory in public flying ubiquitous sensor networks (FUSN-P). In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds.) ruSMART 2015. LNCS, vol. 9247, pp. 352–366. Springer, Cham (2015). Scholar
  16. 16.
    Kim, D.H., Lee, K., Park, M.Y., Lim, J.: UAV-based localization scheme for battlefield environments. In: MILCOM 2013 – 2013 IEEE Military Communications Conference, San Diego, CA, pp. 562–567 (2013)Google Scholar
  17. 17.
    Du, H.J., Lee J.P.Y.: Passive geolocation using TDOA method from UAVs and ship/land-based platforms for maritime and littoral area surveillance. Defence R & D Canada-Ottawa (2004)Google Scholar
  18. 18.
    Mashkov, G., Borisov, E., Fokin, G.: Experimental validation of multipoint joint processing of range measurements via software-defined radio testbed. In: 18th International Conference on Advanced Communication Technology (ICACT), Pyeongchang, pp. 268–273 (2016)Google Scholar
  19. 19.
    Mashkov, G., Borisov, E., Fokin, G.: Positioning accuracy experimental evaluation in SDR-based MLAT with joint processing of range measurements. In: 2016 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET), Jakarta, pp. 7–12 (2016)Google Scholar

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

Personalised recommendations