Skip to main content
Springer Nature Link
Log in

Recurrent Networks for Integrated Navigation

  • Conference paper
Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3498))

Included in the following conference series:

  • 1274 Accesses

Abstract

A novel neural-network-compensated Kalman filter for integrated navigation system was proposed. Based on the similarity of operation principle between Elman networks and non-linear ARMA model, the Elman network is employed as a compensating error estimator to improve accuracy of the Kalman filter. The proposed architecture is evaluated with the acquired data from a naval vessel. And the results show that the presented method can markedly attenuate the effect of interferes to Kalman filter, and improve the precision of the integrated navigation system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Haykin, S.: Kalman Filtering and Neural Networks. John Wiley & Sons, Chichester (2001)

    Book  Google Scholar 

  2. Haykin, S.: Neural Networks, 2nd edn. Prentice-Hall, Englewood Cliffs (1999)

    MATH  Google Scholar 

  3. Yang, M.H., Kriegman, D.J., Ahuja, N.: Detecting Faces in Images: A Survey. IEEE Trans. on Pattern Analysis and Machine Intelligence 24, 34–58 (2002)

    Article  Google Scholar 

  4. Igel, C., Kreutz, M.: Operator Adaptation in Evolutionary Computation and Its Application to Structure Optimization of Neural Networks. Neurocomputing 55, 347–361 (2003)

    Article  Google Scholar 

  5. Elman, J.L.: Finding Structure in Time. Cognitive Science 14, 179–211 (1990)

    Article  Google Scholar 

  6. Connor, J.T., Martin, D., Atlas, L.E.: Recurrent Neural Networks and Robust Time Series Prediction. IEEE Transactions on Neural networks 5, 240–254 (1994)

    Article  Google Scholar 

  7. Gilde, C.: Time Series Analysis and Prediction Using Recurrent Gated Experts. Master’s Thesis, Department Of Computer Science, University of Skövde, Sweden (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Navigation, Dalian Naval Academy, Dalian, Liaoning, 116018, China

    Jianguo Fu, Yingcai Wang, Jianhua Li, Zhenyu Zheng & Xingbo Yin

Authors
  1. Jianguo Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yingcai Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jianhua Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhenyu Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xingbo Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fu, J., Wang, Y., Li, J., Zheng, Z., Yin, X. (2005). Recurrent Networks for Integrated Navigation. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_47

Download citation

  • DOI: https://doi.org/10.1007/11427469_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25914-5

  • Online ISBN: 978-3-540-32069-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics