Jump to ContentJump to Main Navigation
Show Summary Details
In This Section

Annual of Navigation

The Journal of Polish Navigational Forum

1 Issue per year

Open Access
Online
ISSN
2300-6633
See all formats and pricing
In This Section

Indoor Navigation Using Particle Filter and Sensor Fusion

Lukas Köping
  • Würzburg-Schweinfurt - University of Applied Sciences
/ Thomas Mühsam
  • Würzburg-Schweinfurt - University of Applied Sciences
/ Christian Ofenberg
  • Würzburg-Schweinfurt - University of Applied Sciences
/ Bernhard Czech
  • Würzburg-Schweinfurt - University of Applied Sciences
/ Michael Bernard
  • Würzburg-Schweinfurt - University of Applied Sciences
/ Jens Schmer
  • Würzburg-Schweinfurt - University of Applied Sciences
/ Frank Deinzer
  • Würzburg-Schweinfurt - University of Applied Sciences
Published Online: 2013-07-27 | DOI: https://doi.org/10.2478/v10367-012-0016-6

Abstract

In this paper we present an indoor localization system based on particle filter and multiple sensor data like acceleration, angular velocity and compass data. With this approach we tackle the problem of documentation on large building yards during the construction phase. Due to the circumstances of such an environment we cannot rely on any data from GPS, Wi-Fi or RFID. Moreover this work should serve us as a first step towards an all-in-one navigation system for mobile devices. Our experimental results show that we can achieve high accuracy in position estimation.

Keywords: indor navigation; particle filter; sensor fusion; mobile devices

  • [1] Deinzer F., Derichs C., Niemann H., Denzler J., A Framework for Actively Selecting Viewpoints in Object Recognition, International Journal of Pattern Recognition and Artificial Intelligence, 2009, Vol. 23, No. 4, pp. 765-799.Web of ScienceGoogle Scholar

  • [2] Doucet A., Johansen A. M., A tutorial on particle filtering and smoothing: Fifteen years later, Hand-book of Nonlinear Filtering, D. Crisan and B. Rozovsky eds. Oxford, UK, Oxford University Press, 2009.Google Scholar

  • [3] Evennou F., Marx F., Novakov E., Map-aided indoor mobile positioning system using particle filter, Wireless Communications and Networking Conference, 2005, Vol. 4, pp. 2490-2494.Google Scholar

  • [4] Harter A., Hopper A., Steggles P., Ward A., Webster P., The Anatomy of a Context-Aware Application, Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, 1999, pp. 59-68.Google Scholar

  • [5] Isard M., Andrew B., CONDENSATION - Conditional Density Propagation for Visual Tracking, International Journal of Computer Vision, 1998, Vol. 29, No. 1, p. 5.Google Scholar

  • [6] Meng W., Xiao W., Ni W., Lihua X., Secure and robust Wi-Fi fingerprinting indoor localization. International Conference on Indoor Positioning and Indoor Navigation, 2011, pp. 1-7.Google Scholar

  • [7] Retscher G., Fu Q., Continuos Indoor Navigation with RFID and INS, Position Location and Navigation Symposium (PLANS), 2010, pp. 102-112.Google Scholar

  • [8] Song Y., Yu H., A RSS Based Indoor Tracking Algorithm via Particle Filter and Probability Distribution. 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008, pp. 1-4. Google Scholar

About the article

Published Online: 2013-07-27

Published in Print: 2012-12-01


Citation Information: Annual of Navigation, ISSN (Online) 1640-8632, DOI: https://doi.org/10.2478/v10367-012-0016-6.

Export Citation

This content is open access.

Comments (0)

Please log in or register to comment.
Log in