Skip to main content Accesibility Help

Dynamic multipath mitigation applying unscented Kalman filters in local positioning systems

  • Thorsten Nowak (a1) and Andreas Eidloth (a1)

Multipath propagation is still one of the major problems in local positioning systems today. Especially in indoor environments, the received signals are disturbed by blockages and reflections. This can lead to a large bias in the user's time-of-arrival (TOA) value. Thus multipath is the most dominant error source for positioning. In order to improve the positioning performance in multipath environments, recent multipath mitigation algorithms based upon the concept of sequential Bayesian estimation are used. The presented approach tries to overcome the multipath problem by estimating the channel dynamics, using unscented Kalman filters (UKF). Simulations on artificial and measured channels from indoor as well as outdoor environments show the profit of the proposed estimator model. Furthermore, the quality of channel estimation applying the UKF and the channel sounding capabilities of the estimator are shown.

Corresponding author
Corresponding author: T. Nowak Email:
Hide All
[1]Fenton, P.; Jones, J.: The theory and performance of NovaTel Inc.'s vision correlator, in Proc. 18th Int. Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2005), Long Beach, CA, USA, September 2005.
[2]Jones, J.; Fenton, P.; Smith, B.: Performance evaluation of the multipath estimating delay lock loop, Technical report, NovAtel, Calgary, Alberta, Canada, June 2004.
[3]Townsend, B.R.; van Nee, D.J.R.; Fenton, P.C.; Van Dierendonck, K.J.: Performance evaluation of the multipath estimating delay lock loop, in Proc. IEEE Position, Location and Navigation Symp. 1994, Las Vegas, NV, USA, January 1994.
[4]van Dierendonck, A.J.; Fenton, P.; Ford, T.: Theory and performance of narrow correlator spacing in a GPS receiver, in Proc. ION National Technical Meeting, San Diego, CA, USA, January 1992.
[5]Weill, L.R.: Achieving theoretical accuracy limits for pseudo ranging in the presence of multipath, in Proc. 8th Int. Technical Meeting of the Satellite of the Institute of Navigation (ION GPS’95), Palm Springs, CA, USA, 1995, 15211530.
[6]Iltis, R.A.: Joint estimation of PN code delay and multipath using the extended Kalman filter. IEEE Trans. Commun., 38 (10) (1990), 16771685.
[7]Hofmann, G.: Forschungsbericht TOA-Schätzung bei Mehrwegeausbreitung, Technical Report, Fraunhofer Institute for Integrated Circiuts, February 2007.
[8]Hofmann, G.; Breiling, M.: Vorrichtung und Verfahren zum Bestimmen eines Eintreffzeitpunktes einer Empfangsfolge, 2006, DE 10 2004 059 941 A1.
[9]Rohmer, S.K.G.; Dünkler, R.; von der Grün, T.: A microwave based tracking system for soccer, in Proc. 18th Int. Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2005), Long Beach, CA, USA, September 2005.
[10]Lentmaier, M.; Krach, B.; Robertson, P.: Bayesian time delay estimation of GNSS signals in dynamic multipath environments. Int. J. of Navig. Observ., 2008 (2008), 7282.
[11]Lentmaier, M.; Krach, B.; Robertson, P.; Thiasiriphet, T.: Dynamic multipath estimation by sequential Monte Carlo methods. in Proc. 20th Int. Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2007), September 2007, 17121721.
[12]Särkkä, S.; Tamminen, T.; Vehtari, A.; Lampinen, J.: Probabilistic Methods in Multiple Target Tracking – Review and Bibliography, Technical Report B36, Laboratory of Computational Engineering, Helsinki University of Technology, February 2004, Research Report B36.
[13]Bar-Shalom, Y.; Li, X.-R.; Kirubarajan, T.: Estimation with Applications to Tracking and Navigation. Wiley Interscience, New York, 2001.
[14]van der Heijden, F.; Duin, R.P.W.; de Ridder, D.; Tax, D.M.J.: Classification, Parameter Estimation and State Estimation–An Engineering Approach Using Matlab, John Wiley & Sons, Ltd., New York, 2004.
[15]van der Merwe, R.: Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models, Ph.D. Thesis, OGI School of Science & Engineering, Oregon Health & Science University, Portland, OR, April 2004.
[16]Kalman, R.E.: A new approach to linear filtering and prediction problems. Trans. ASME, J. Basic Eng. D, 82 (1960), 3545.
[17]Julier, S.J.; Uhlmann, J.K.: A new extension of the Kalman filter to nonlinear systems, in Int. Symp. Aerospace/Defense Sensing, Simul. and Controls, Orlando, FL, USA, 1997.
[18]Julier, S.J.; Uhlmann, J.K.; Durrant-Whyte, H.F.: A new approach for filtering nonlinear systems, in Proc. American Control Conf., 1995, vol. 3, 1995, 16281632.
[19]van der Merwe, R.; Wan, E.A.; Julier, S.I.: Sigma-point Kalman filters for nonlinear estimation and sensor-fusion: applications to integrated navigation. in Proc. AIAA Guidance, Navigation & Control Conf., 2004, 1619.
[20]Wan, E.A.; van der Merwe, R.: The unscented Kalman filter for nonlinear estimation, in Proc. Symp. 2000 on Adaptive Systems for Signal Processing, Communication and Control (AS-SPCC), Lake Louise, Alberta, Canada, October 2000, IEEE.
[21]Hartikainen, J.; Särkkä, S.: Optimal Filtering with Kalman Filters and Smoothers a Manual for Matlab Toolbox EKF/UKF., February 2008, Department of Biomedical Engineering and Computational Science, Helsinki University of Technology.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

International Journal of Microwave and Wireless Technologies
  • ISSN: 1759-0787
  • EISSN: 1759-0795
  • URL: /core/journals/international-journal-of-microwave-and-wireless-technologies
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed