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      Whitening Degree Evaluation Method to Test Estimate Accuracy of Speckle Covariance Matrix

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          Abstract

          In the background of sea clutter, the accuracy of adaptive target detection is heavily influenced by the estimated performance of speckle covariance matrix. Generally, Normalized Frobenius Norm (NFN) is used to test the estimated accuracy of different speckle covariance matrix estimators, in which the requirement of a known real covariance matrix is hardly realized in the radar system. Therefore, in this study, a whitening degree evaluation method is proposed wherein the decorrelation of speckle covariance matrix in whitening filter processing of the radar system is fully exploited. It considers the correlation degree among pulses in the whitening clutter vector as the criterion to evaluate the estimate error of the speckle covariance matrix. The proposed method shows consistent conclusions with NFN on simulated data and also avoids limitations of the latter method in real data processing.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 June 2017
          : 6
          : 3
          : 285-291
          Article
          fe3adc4dc9bf4fbb86f51525346e28e6
          10.12000/JR16146
          e2593a30-ac67-4249-9c2d-b3ade5c52a05

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          History
          Categories
          Technology (General)
          T1-995

          Remote sensing,Electrical engineering
          Real covariance matrix,Normalized Frobenius Norm (NFN),Whitening degree evaluation,Covariance matrix estimation

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