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Author:

Xu, L.-J. (Xu, L.-J..) | Chen, Y.-Z. (Chen, Y.-Z..) (Scholars:陈阳舟) | Cui, P.-Y. (Cui, P.-Y..)

Indexed by:

Scopus PKU CSCD

Abstract:

In order to resolve the shortcoming of the traditional federal Kalman filtering, a new method is presented in which the fuzzy reasoning system is combined with the traditional Kalman technology. This method can modify the statistical characteristic of noises on real time. It can not only modify the local filter but also bring forward a bran-new information fusion arithmetic which is applied to central filter. A fuzzy reasoning system is built to obtain different weights of the all states estimate values that are based on the actual circumstance and fuse these values. Then the complicated calculation is avoided and precision is advanced. At last the new means is applied in the INS/GPS Integrated Navigation system and the result of computer simulation indicates that it is useful with high effectiveness and practical.

Keyword:

Federal Kalman filtering; Fuzzy reasoning system; Information fusion; Integrated navigation

Author Community:

  • [ 1 ] [Xu, L.-J.]Coll. of Info. and Technology, Sichuan Agriculture Univ., Yaan 625000, China
  • [ 2 ] [Xu, L.-J.]Coll. of Electronic Information, Beijing Univ. of Technology, Beijing 100022, China
  • [ 3 ] [Chen, Y.-Z.]Coll. of Electronic Information, Beijing Univ. of Technology, Beijing 100022, China
  • [ 4 ] [Cui, P.-Y.]Coll. of Electronic Information, Beijing Univ. of Technology, Beijing 100022, China

Reprint Author's Address:

  • [Xu, L.-J.]Coll. of Info. and Technology, Sichuan Agriculture Univ., Yaan 625000, China

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Source :

Journal of System Simulation

ISSN: 1004-731X

Year: 2005

Issue: 1

Volume: 17

Page: 124-128

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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