IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v181y2019i2d10.1007_s10957-018-01466-8.html
   My bibliography  Save this article

Cognitive Design of Radar Waveform and the Receive Filter for Multitarget Parameter Estimation

Author

Listed:
  • Yu Yao

    (East China Jiaotong University)

  • Junhui Zhao

    (East China Jiaotong University)

  • Lenan Wu

    (Southeast University)

Abstract

This research work considers waveform design for an adaptive radar system. The aim is to achieve enhanced feature extraction performance for multiple extended targets. There are two scenarios to consider: multiple extended targets separated in range and multiple extended targets close in range. We propose a waveform optimization scheme based on Kalman filtering by minimizing the mean square error of separated target scattering coefficient estimation and a waveform optimization approach by minimizing the mean square error of closed power spectrum density estimation. A convex cost function is established, and the optimal solution can be obtained using the existing convex programming algorithm. With subsequent iterations of the algorithm, the simulation results demonstrate an improvement in the estimation of target parameters from the dynamic scene, such as target scattering coefficient and power spectrum density, while maintaining relatively lower computational complexity.

Suggested Citation

  • Yu Yao & Junhui Zhao & Lenan Wu, 2019. "Cognitive Design of Radar Waveform and the Receive Filter for Multitarget Parameter Estimation," Journal of Optimization Theory and Applications, Springer, vol. 181(2), pages 684-705, May.
  • Handle: RePEc:spr:joptap:v:181:y:2019:i:2:d:10.1007_s10957-018-01466-8
    DOI: 10.1007/s10957-018-01466-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-018-01466-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10957-018-01466-8?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Omid Pakdel Azar & Hadi Amiri & Farbod Razzazi, 2021. "Enhanced target detection using a new combined sonar waveform design," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 77(2), pages 317-334, June.

    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:spr:joptap:v:181:y:2019:i:2:d:10.1007_s10957-018-01466-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.