Browse > Article
http://dx.doi.org/10.5391/JKIIS.2009.19.3.408

GPS/INS Data Fusion and Localization using Fuzzy Inference/UPF  

Lee, So-Hee (국방대학교 전산정보학과)
Yoon, Hee-Byung (국방대학교 전산정보학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.19, no.3, 2009 , pp. 408-414 More about this Journal
Abstract
A GPS/INS system is widely used in the UGV to estimate position during the mission. However, there are few restrictions when a GPS/INS system used alone. For example, GPS provides precise location information but easily interrupted by external factors like weather, environment, etc. INS provides continuous location data but positioning errors grew very rapidly with time. Therefore, it is necessary to integrating multi-sensors for more continuous and correct position estimation. In this paper, we propose location estimation algorithm of the UGV for GPS/INS integrated system that combines Fuzzy Inference and Unscented Particle Filter(UPF) to improve navigation. Fuzzy inference provides the simplest method integrating GPS/INS and UPF is non-linear estimation filter well suited to the correction of errors. The performance of the proposed algorithm was tested to compare with other algorithms. the results show that the proposed algorithm is more accuracy in position estimation and ensures continuous position tracking.
Keywords
GPS; INS; Unscented Particle Filter; Fuzzy inference; Fusion algorithm; UGV;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Francois Caron et al., 'GPS/INS data fusion using multisensory kalman filtering: introduction of contextual aspects,' Information Fusion 7, pp.221-230, 2006   DOI   ScienceOn
2 M. Mamdani, 'Application of fuzzy algorithm for control of simple dynamic plant,' Proc IEEE 121, pp.1585-1588, 1974
3 D.H. Titterton and J.L. Weston, 'Strapdown Inertial Navigation Technology,' IEEE Radar, Sonar, Navigation and Avionics Series, 1997
4 B.W. Leach, R. Rahbari, and J. Dillon, 'Low cost strapdown IMU/DGPS integrated navigator with fuzzy logic adaptive tunning,' 9th Saint Petersburg International Conference on Integrated Navigation System, Saint Perterburg, pp.264-273, 2002
5 B. W. Parkinson et al., Global Positioning System: Theory and Application, vol.I&II, American Institute of Aeronautics and Astronautics. Inc., 1996
6 N.J. Gordon, D.J. Salmond, and A.F.M. Smith, 'Novel approach to nonlinear/non-Gaussian Bayesian state estimation,' IEEE Proceedings on Radar and Signal Processing, vol. 140, pp.107-113, 1993   DOI   ScienceOn
7 Yunsu Bok et al., 'UGV Localization based on Scene Matching and Pose Estimation,' Proceedings of 2007 Annual Conference, KIMST, pp.1144-1150, 2007
8 J.Z. Sasiadek and Q. Wang, 'Low cost automation using GPS/INS data fusion for accurate positioning,' Robotica, vol. 21, pp.255-260, 2003   DOI   ScienceOn
9 H.S. Hwang, Fuzzy, Evolutionary Computing Programming, Naeha Publication, 2006
10 Elliott D. Kaplan, Understanding GPS Principles and Applications, Artech House, Inc., 1996
11 N.J. Gordon, D.J. Salmond, and A.F.M. Smith, 'Novel approach to nonlinear/non-Gaussian Bayesian state estimation,' IEEE Proceedings on Radar and Signal Processing, vol. 140, pp.107-113, 1993   DOI   ScienceOn
12 A.D. King, 'Inertial navigation-Forty Years of Evolution,' GEC Review, vol. 13, no. 3, 1998