A fuzzy adaptive GPS/INS integrated navigation algorithm

Mingwei Liu, Fenfen Xiong*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

15 Citations (Scopus)

Abstract

The statistical properties of the measurement noise of the missile-borne navigation system would vary under different actual working conditions. To address this issue, a fuzzy logic adaptive Kalman filtering based missile-borne GPS/INS integrated navigation algorithm is proposed in this paper. By monitoring the output parameter PDOP of the GPS receiver, the fuzzy logic adaptive controller is utilized to modify the measurement noise variance of the Kalman filter. Thus the Kalman filter can be adjusted to the optimal state, which eventually improves the accuracy of the integrated navigation system. The simulation results show that the proposed algorithm has strong adaptability to the time-varying measurement noise, and outperforms the conventional Kalman filter algorithm by providing more accurate solutions.

Original languageEnglish
Pages (from-to)660-664
Number of pages5
JournalProcedia Engineering
Volume15
DOIs
Publication statusPublished - 2011
Event2011 International Conference on Advanced in Control Engineering and Information Science, CEIS 2011 - Dali, Yunnam, China
Duration: 18 Aug 201119 Aug 2011

Keywords

  • Fuzzy adaptive algorithm
  • Integrated navigation
  • Kalman filtering
  • Position dilution of precision (PDOP)

Fingerprint

Dive into the research topics of 'A fuzzy adaptive GPS/INS integrated navigation algorithm'. Together they form a unique fingerprint.

Cite this

Liu, M., & Xiong, F. (2011). A fuzzy adaptive GPS/INS integrated navigation algorithm. Procedia Engineering, 15, 660-664. https://doi.org/10.1016/j.proeng.2011.08.123