Preview

Giroskopiya i Navigatsiya

Advanced search

Применение парциальных фильтров в алгоритме навигации с использованием карты местности

Abstract

This article presents the numerical approach to map-matching problem. The proposed solution is based on sequential Monte Carlo method, so called particle filtering. This algorithm can be adapted for implementation on real-time portable car navigation systems equipped with GPS or dead reckoning sensors. The algorithm reliability and accuracy performance was investigated using simulated data and data from real-world driving tests in urban environment.

About the Authors

П. Дэвидсон
Технический университет г. Тампере
Finland


Ю. Колин
Технический университет г. Тампере
Russian Federation


Я. Такала
Технический университет г. Тампере
Finland


References

1. French, R.L., Land vehicle navigation and tracking // Global Positioning System: Theory and Applications, vol. 2, pp. 275-301, 1996.

2. Dmitriev, S., Stepanov, O., Rivkin, B., Koshaev, D., Optimal map-matching for car navigation system, in Proc. of 6th International Conference on Integrated Navigation Systems, St. Petersburg 1999.

3. Scott, C., Improved GPS positioning for motor vehicles through map matching, in Proc. of ION GPS-94, Salt Lake City, UT, 1994, pp. 1019-1028.

4. Zhao, Y., Vehicle Location and Navigation System // Artech House, pp. 83-103, 1997.

5. Arulampalam, M. S., Maskell, S., Gordon, N., and Clapp, T., A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking // IEEE Transactions on Signal Processing, vol. 50, no. 2, Feb. 2002.

6. Gustafsson, F., Gunnarsson, F., Bergman, N., Forssell, U., Jansson, J., Karlsson, R., and Nordlund, P.-J., Particle filters for positioning, navigation, and tracking // IEEE Transactions on Signal Processing, vol. 50, no. 2, Feb. 2002.

7. Fouque, C., Bonnifait, P., and Bétaille, D., Enhancement of global vehicle localization using navigable road maps and dead-reckoning, in Proc. of ION Position, Location and Navigation Symposium, 2008.

8. Syed, S. and Cannon, M.E., Fuzzy logic-based map matching algorithm for vehicle navigation system in urban canyons,” in Proc. ION National Technical Meeting, San Diego, CA, Jan. 26-28, 2004.

9. Kim, S. and Kim, J.-H., Adaptive fuzzy-network-based C-measure map-matching algorithm for car navigation system, IEEE Transactions on Industrial Electronics, vol. 48, no. 2, Apr. 2001.

10. Quddus, M.A., Ochieng, W.Y., Zhao, L., Noland, R.B., A general map matching algorithm for transport telematics applications // GPS Solutions, vol. 7, no. 3, pp. 157-167, 2003.

11. Grush, B., Road tolling isn’t navigation, European Journal of Navigation, vol. 6, no 1, Feb. 2008.

12. OpenStreetMap, http://www.openstreetmap.org/

13. Doucet A., Godsill S., and Andrieu C., On sequential Monte Carlo sampling methods for Bayesian filtering // Statistics and Computing (2000) 10, рр. 197–208.


Review

For citations:


 ,  ,   . Giroskopiya i Navigatsiya. 2011;19(3):48-58. (In Russ.)

Views: 13

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 0869-7035 (Print)
ISSN 2075-0927 (Online)