Logo PTI Logo FedCSIS

Proceedings of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 30

Location Accuracy of a Ground Station based on RSS in the Rice Channel

DOI: http://dx.doi.org/10.15439/2022F15

Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 577–580 ()

Full text

Abstract. The article presents the assessment of the potential accuracy of the location of the terrestrial radio signal source in the Rice channel using the received signal filtering and the non-linear regression function. The basic assumption for the parameterization of the channel was to use a drone with a simple antenna system and RSS analysis from multiple measurement points (Multilateration location). Preliminary results under Rice-typical channel conditions indicate position estimation errors of the order of 60 meters for K = 7, which in the assumed network structure is approximately 10\% of the actual average distance. By using properly parameterized filtration systems (Kalman algorithm and Moving Average algorithm set), it is possible to increase this accuracy by one-third of the initial value.

References

  1. H. Wang, H. Zhao, J. Zhang. D. Ma, J. Li, J. Wei, „Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System Perspective,” IEEE Communications Surveys & Tuturials, pp. 1027-170, vol.22, No.2, 2020 http://dx.doi.org/10.1109/COMST.2019.2962207.
  2. T. D. Chuyen, H. V. Huy, T. L. Nguyen, „Control design of an UAV–Q based on feedback linearization and optimum modulus methods,” w Proceedings of the Sixth International Conference on Research in Intelligent and Computing, 2021, http://dx.doi.org/10.15439/2021R20.
  3. T. Adam, F. Babič, „UAV Mission Definition and Implementation for Visual Inspection,” w Proceedings of the 16th Conference on Computer Science and Intelligence Systems, 2021, http://dx.doi.org/10.15439/2021F24.
  4. N. Boonyyathanming, S. Gongmenee, P. Kayunyeam, P. Wutticho, S. Prongnuch, „Design and Implementation of Mini-UAV for Indoor Surveillance,” International Electrical Engeneering Congress, 10-12 March 2021, http://dx.doi.org/10.1109/iEECON51072.2021.9440350.
  5. S. Gupte, P.I.T. Mohondas, J.M. Conred, „A Survey of Quadrotor Unmanned Aerial Vehicles,” IEEE Xplore, 2012, http://dx.doi.org/10.1109/SECon.2012.6196930.
  6. C.D. Morales, D. Guevara, M.A. Truvol, „Using Terrestrial Radio Links to Multilateration Techniques,” IEEE COLCOM, 2016, http://dx.doi.org/10.1109/ColComCon.2016.7516389.
  7. J. Michalak, „Efficiency of selected drone flight algorithms in increasing the level of ad-hoc network connectivity without knowing the location of disconnected nodes,” 37th International Business Information Management Conference (IBIMA), May 2021.
  8. S. Goswami, Indoor Location Techniques, Milpitas: Springer, 2013, http://dx.doi.org/10.1007/978-1-4614-1377-6.
  9. Ed. H.A. Karimi, Advanced Locatin-Based Technologies and Services, London: CRC Press, 2013.
  10. Ed. S.A.Zekavat, R.M. Buehrer, Handbook of Position Location, Hoboken: Wiley, 2012.
  11. Y. Liu, Z. Yang, Locatin, Localization and Localizabiility, London: Springer, 2011, http://dx.doi.org/10.1007/978-1-4419-7371-9.
  12. R.A. Poisel, Electronic Warfare Target Location Methods, Boston, London: Artech House, 2012.
  13. F. Zafari, A. Gkelias, K.K. Leung, „A Survey of Indoor Localization Systems and Technologies,” IEEE Communications Surveys & Tuturials, 2019, http://dx.doi.org/10.1109/COMST.2019.2911558.
  14. S. Uluscan, T. Filik, „A Survey on the Fundamentals of RSS based Localization,” 2016, http://dx.doi.org/10.1109/SIU.2016.7496069.
  15. N. Saeed , H. Nam, T. Y. Al-Naffouri , M. S. Alouini, „A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques,” IEEE Communications Surveys & Tuturials, Vol.21 2019, http://dx.doi.org/10.1109/COMST.2019.2921972.
  16. S. Bohidar, S Behera, C. R. Tripathy, „A Comparative View on Received Signal Strength (RSS) Based location Estimation in WSN,” IEEE International Conference on Engineering and Technology (ICETECH), March\ 2015, http://dx.doi.org/10.1109/ICETECH.2015.7275032.
  17. Q.Duy, P.De, „A Survey of Fingerprint-Based Outdoor Localization,” IEEE Communications Surveys & Tutarials, 2016, http://dx.doi.org/10.1109/COMST.2015.2448632.
  18. J. Michalak, „Location accuracy of a radio ground station in the Rice channel by the multilateration method with the use of non-linear regression function,” 39th International Business Information Management Conference (IBIMA), April 2022.
  19. O.S. Oguejiofor, A.N. Aniedu, H.C., Ejiofor, A.U. Okolibe, „Trilateration Based localization Algorithm for Wireless Sensor Network,” International Journal of Science and Modern Engineering, Vol.1, Issue 10 September 2013.
  20. W. Khawaya, I. Guvenc, D.W. Matolak, U.C. Fiebig, N. Schneckenburger, „A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles,” IEEE Communicaitons Surveys & Tutorials, Vol.21, No.3 2019, http://dx.doi.org/10.1109/COMST.2019.2915069.
  21. Y.Diang, Y. Xiao, J. Xie, T. Zhang, „A Time-varying Transition Channel Model for Air-Ground Communication,” IEEE Xplore, 2017, http://dx.doi.org/10.1109/DASC.2017.8102055.
  22. M.S. Grewal, A.P. Andrews, „Kalman Filtering, Theory and Practice Using MATLAB,” by John Wiley & Sons, Inc., 2015.
  23. M.N. Rahman, I.A.T. Hanuranto, R. Mayasari, „Trilateration and Iterative Multilateration Algorithm for Localization Schemes on Wireless Sensor Network,” International Conference on Control, Electronics, Renewable Energy and Communications, 2017, http://dx.doi.org/10.1109/ICCEREC.2017.8226710.
  24. A. Norrdine, „An Algebraic Solution to the Multilatration Problem,” International Conference on Indoor Positioning and Indoor Navigation, 13-15 November 2012.