Robust adaptive detection of buried pipes using GPR
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- 作者：Q. Hoaraua ; quentin.hoarau@univ-smb.fr" class="auth_mail" title="E-mail the corresponding author ; G. Ginolhaca ; guillaume.ginolhac@univ-smb.fr" class="auth_mail" title="E-mail the corresponding author ; A.M. Attoa ; abdourrahmane.atto@univ-smb.fr" class="auth_mail" title="E-mail the corresponding author ; J.M. Nicolasb ; jean-marie.nicolas@telecom-paristech.fr" class="auth_mail" title="E-mail the corresponding author
- 关键词：GPR ; Buried pipes ; Adaptive detection ; Covariance matrix ; Non-Gaussian ; Regularised covariance matrix estimator
- 刊名：Signal Processing
- 出版年：2017
- 出版时间：March 2017
- 年：2017
- 卷：132
- 期：Complete
- 页码：293-305
- 全文大小：4805 K
文摘
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A new adaptive detector is proposed for GPR buried object detection.
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A statistical noise model is used to help mitigate noise contributions.
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Regularised covariance matrix estimators are proposed for GPR image analysis.
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Optimal and simulated parameter values ensure the detector that stays CFAR.
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Low response level objects detection is enhanced.