Knowledge-Aided Adaptive Detection of Radar Target in Gaussian Clutter
ID:41 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:00 Hits:1027 Oral Presentation

Start Time:2020-06-09 15:00(Asia/Shanghai)

Duration:20min

Session:R Regular Session » R12Target Detection and Localization II

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Abstract
This paper presents an adaptive detection method of radar target using the priori knowledge of Gaussian clutter. It is assumed that the clutter covariance matrix is random and obeys the inverse complex Wishart distribution. Based on the priori knowledge, we propose an adaptive detector via utilizing the generalized likelihood ratio test. The proposed adaptive detector does not need training data and detection performance can be achieved due to the use of a prior knowledge about the clutter. Finally, the detection performance of the proposed detector is evaluated and the results illustrate that the proposed detector is superior to the conventional counterparts, particularly for small sample number of the received signal.
Keywords
Target detection; Priori knowledge; MIMO radar
Speaker
Xinyu Zhang
Lanzhou University, China

Submission Author
Xinyu Zhang Lanzhou University, China
Jin-wang Han Beijing Huahang Radio Measurements Research Institute, China
XinLiang Zhang Beihang University, China
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Important Date
  • Conference Date

    Jun 08

    2020

    to

    Jun 11

    2020

  • Jan 12 2020

    Draft paper submission deadline

  • Apr 15 2020

    Early Bird Registration

  • Dec 31 2020

    Registration deadline

Sponsored By
IEEE Signal Processing Society
Organized By
Zhejiang University
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