Persymmetric Subspace Rao and Wald Tests for Distributed Target in Partially Homogeneous Environment
ID:134 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:28 Hits:368 Oral Presentation

Start Time:2020-06-08 15:40(Asia/Shanghai)

Duration:20min

Session:S Special Session » SS07Advanced Techniques In Radar Detection, Localization, And Electronic Counter-Measures

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Abstract
We consider the problem of distributed target detection in partially homogeneous Gaussian clutter with unknown covariance matrix. The target is assumed to lie in a multi-rank subspace with unknown coordinates. By incorporating the persymmetric structure of the covariance matrix into the detector design, we devise a persymmetric subspace Rao detector (Per-Rao) and a persymmetric subspace Wald detector (Per-Wald). It is remarkable that the Per-Rao coincide with the Per-Wald in the partially homogeneous environment, and both detectors are shown to ensure constant false alarm rate (CFAR) with respect to the covariance matrix. Numerical examples verify the superiority of the proposed methods in training-restricted situations.
Keywords
Adaptive detection; Rao test; Wald test; distributed target; non-homogeneity
Speaker
Yongchan Gao
Xidian University, China

Submission Author
Yongchan Gao Xidian University, China
Linlin Mao Institute of Acoustics, Chinese Academy of Sciences, China
Hongbing Ji School of Electronic Engineering, Xidian University, China
Liyan Pan Xidian University, China
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    Jun 08

    2020

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    Jun 11

    2020

  • Jan 12 2020

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