IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3625362.html
   My bibliography  Save this article

A Dynamic-Weighted Attenuation Memory Extended Kalman Filter Algorithm and Its Application in the Underwater Positioning

Author

Listed:
  • Bo Guo
  • Jianye Ma
  • Cui Wang

Abstract

Extended Kalman filter (EKF) plays an important role in the acoustic signal processing of underwater positioning. However, accumulative errors and model inaccuracies lead to divergence. Then, attenuation memory EKF is created in response to this issue which needs to manually select all or part of the parameters. Thus, a dynamic-weighted attenuation memory EKF is proposed . Firstly, several underwater positioning simulations under different conditions are carried out. Results show, with the change of parameter conditions in positioning, the ideal attenuation coefficient changes between 0.5 and 1, but it is difficult to express it in function formula or statistical form. Secondly, a dynamic selection method of attenuation factor is designed. In the later contrast simulation, the proposed method has improved the positioning performance compared with the existing attenuation memory filter algorithm. Finally, the results of physical model verification experiment show that the dynamic-weighted attenuation memory EKF algorithm not only suppresses divergence better but also avoids the subjectivity of attenuation coefficient selection to a certain extent.

Suggested Citation

  • Bo Guo & Jianye Ma & Cui Wang, 2021. "A Dynamic-Weighted Attenuation Memory Extended Kalman Filter Algorithm and Its Application in the Underwater Positioning," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-11, February.
    • Handle: RePEc:hin:jnlmpe:3625362
    DOI: 10.1155/2021/3625362
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/3625362.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2021/3625362.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/3625362?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:3625362. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.