IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/5252487.html
   My bibliography  Save this article

High Degree Cubature Federated Filter for Multisensor Information Fusion with Correlated Noises

Author

Listed:
  • Lijun Wang
  • Sisi Wang

Abstract

This paper proposes an improved high degree cubature federated filter for the nonlinear fusion system with cross-correlation between process and measurement noises at the same time using the fifth-degree cubature rule and the decorrelated principle in its local filters. The master filter of the federated filter adopts the no-reset mode to fuse local estimates of local filters to generate a global estimate according to the scalar weighted rule. The air-traffic maneuvering target tracking simulations are performed between the proposed filter and the fifth-degree cubature federated filter. Simulations results demonstrate that the proposed filter not only can achieve almost the same accuracy as the fifth-degree cubature federated filter with independent white noises, but also has superior performance to the fifth-degree cubature federated filter while the noises are cross-correlated at the same time.

Suggested Citation

  • Lijun Wang & Sisi Wang, 2016. "High Degree Cubature Federated Filter for Multisensor Information Fusion with Correlated Noises," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-7, August.
    • Handle: RePEc:hin:jnlmpe:5252487
    DOI: 10.1155/2016/5252487
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2016/5252487.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2016/5252487.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2016/5252487?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:5252487. 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.