IDEAS home Printed from https://ideas.repec.org/a/igg/jdst00/v13y2022i5p1-22.html
   My bibliography  Save this article

Moving Target Detection Using Fuzzy Bayesian Fusion in Multichannel SAR Framework

Author

Listed:
  • Bharat Kumar M.

    (Department of Electronics and communication Engineering, A. U. College of Engineering, Andhra Pradesh, India)

  • Rajesh Kumar P.

    (Department of Electronics and Communication Engineering,A. U. College of Engineering, Andhra Pradesh, India)

Abstract

In this paper, a novel FBF-MTD is proposed for the detection of moving target by integrating the fuzzy concept in Bayesian fusion model. This method uses the decision fusion method that combines the matching filter, Fourier transform and the STFT. In the first step, acceleration, velocity, and RCS are simulated and the radar that returns from the target is calculated based on transmission power, distance of target, antenna gain, and RCS. Then, the FBF-MTD method combines the results of Fourier transform, short time Fourier transform, and matched filter, to produce the final decision. The performance of the proposed FBF-MTD method is analyzed with respect to the metrics, namely detection time, missed target rate, and MSE. The proposed FBF-MTD model obtained the detection time, missed target rate, and MSE values of 3.2495 sec, 0.0524, and 3344.04, respectively that show the superiority of the FBF-MTD model in MTD.

Suggested Citation

  • Bharat Kumar M. & Rajesh Kumar P., 2022. "Moving Target Detection Using Fuzzy Bayesian Fusion in Multichannel SAR Framework," International Journal of Distributed Systems and Technologies (IJDST), IGI Global, vol. 13(5), pages 1-22, January.
  • Handle: RePEc:igg:jdst00:v:13:y:2022:i:5:p:1-22
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJDST.300355
    Download Restriction: no
    ---><---

    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:igg:jdst00:v:13:y:2022:i:5:p:1-22. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.