IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8681418.html
   My bibliography  Save this article

The Advanced Algorithmic Method for Navigation System Correction of Spacecraft

Author

Listed:
  • Danhe Chen
  • K. A. Neusypin
  • Xiang Zhang
  • Chuangge Wang

Abstract

In this paper an advanced method for the navigation system correction of a spacecraft using an error prediction model of the system is proposed. Measuring complexes have been applied to determine the parameters of a spacecraft and the processing of signals from multiple measurement systems is carried out. Under the condition of interference in flight, when the signals of external system (such as GPS) disappear, the correction of navigation system in autonomous mode is considered to be performed using an error prediction model. A modified Volterra neural network based on the self-organization algorithm is proposed in order to build the prediction model, and the modification of algorithm indicates speeding up the neural network. Also, three approaches for accelerating the neural network have been developed; two examples of the sequential and parallel implementation speed of the system are presented by using the improved algorithm. In addition, simulation for a returning spacecraft to atmosphere is performed to verify the effectiveness of the proposed algorithm for correction of navigation system.

Suggested Citation

  • Danhe Chen & K. A. Neusypin & Xiang Zhang & Chuangge Wang, 2019. "The Advanced Algorithmic Method for Navigation System Correction of Spacecraft," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, July.
    • Handle: RePEc:hin:jnlmpe:8681418
    DOI: 10.1155/2019/8681418
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2019/8681418.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2019/8681418.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2019/8681418?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:8681418. 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.