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Author:

Gao, Qiang (Gao, Qiang.) | Jin, Shan (Jin, Shan.) | Wang, Tieliu (Wang, Tieliu.)

Indexed by:

CPCI-S EI Scopus

Abstract:

The GPS / INS integrated navigation system performance will significantly decrease during GPS outages. In this paper, we study an new integrated navigation algorithm based on Adaptive Neural- fuzzy Inference System (ANFIS). The algorithm adopted Kalman filter with pseudo-range and pseudo-range rate observations when the number of GPS satellites was not less 4. Otherwise, ANFIS was used to estimate the navigation errors and restrain the increasing INS errors to achieve integrated navigation. The new algorithm can improve the performance of integrated system effectively and enhance the horizontal position accuracy than traditional tight integration algorithms. Especially, the method is applicable to the complex work environment of navigation systems of ships.

Keyword:

kalman filtering tight integration integrated navigatio adaptive neuro-fuzzy inference system

Author Community:

  • [ 1 ] [Gao, Qiang]Beijing Univ Technol, Coll Elect Info & Control Engn, Beijing, Peoples R China
  • [ 2 ] [Jin, Shan]Beijing Univ Technol, Coll Elect Info & Control Engn, Beijing, Peoples R China
  • [ 3 ] [Wang, Tieliu]Beijing Univ Technol, Coll Elect Info & Control Engn, Beijing, Peoples R China

Reprint Author's Address:

  • [Gao, Qiang]Beijing Univ Technol, Coll Elect Info & Control Engn, Beijing, Peoples R China

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Source :

MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8

ISSN: 1022-6680

Year: 2012

Volume: 433-440

Page: 4065-4070

Language: English

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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