Indoor navigation using particle filter and sensor fusion

• Autorzy: Köping L. , Mühsam T. , Ofenberg C. , Czech B. , Bernard M. , Schmera J. , Deinzer F.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

indoor navigation; particle filter; sensor fusion; mobile devices

• Wydawca: Polskie Forum Nawigacyjne
• Czasopismo: Annual of Navigation
• Rocznik: 2012
• Tom: No. 19, part 2
• Strony: 31--40
• Opis fizyczny: Bibliogr. 8 poz., rys.

Twórcy

autor

Köping L.

• Würzburg-Schweinfurt - University of Applied Sciences

autor

Mühsam T.

• Würzburg-Schweinfurt - University of Applied Sciences

autor

Ofenberg C.

• Würzburg-Schweinfurt - University of Applied Sciences

autor

Czech B.

• Würzburg-Schweinfurt - University of Applied Sciences

autor

Bernard M.

• Würzburg-Schweinfurt - University of Applied Sciences

autor

Schmera J.

• Würzburg-Schweinfurt - University of Applied Sciences

autor

Deinzer F.

• Würzburg-Schweinfurt - University of Applied Sciences

Bibliografia

• [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.
• [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.
• [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.
• [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.
• [5] Isard M., Andrew B., CONDENSATION - Conditional Density Propagation for Visual Tracking, International Journal of Computer Vision, 1998, Vol. 29, No. 1, p. 5.
• [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.
• [7] Retscher G., Fu Q., Continuos Indoor Navigation with RFID and INS, Position Location and Navigation Symposium (PLANS), 2010, pp. 102-112.
• [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.