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A CLUTTER SUPPRESSION METHOD BASED ON IMPROVED PRINCIPAL COMPONENT SELECTION RULE FOR GROUND PENETRATING RADAR

By J. Zhu, W. Xue, X. Rong, and Y. Yu

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Abstract:
Principal component analysis is usually used for clutter suppression of ground penetrating radar, but its performance is influenced by the selection of main components of target signal. In the paper, an improved principal component selection rule is proposed for selecting the main components of target signal. In the method, firstly difference spectrum of singular value is used to extract direct wave and strong target signal, and then, Fuzzy-C means clustering algorithm is used to determine the weights of principal component of weak target signal. Finally, the principal components of strong target signal and weak target signal are reconstructed to obtain target signal. Experimental results show that the proposed method can effectively remove the clutter signals and reserve more target information.

Citation:
J. Zhu, W. Xue, X. Rong, and Y. Yu, "A Clutter Suppression Method Based on Improved Principal Component Selection Rule for Ground Penetrating Radar," Progress In Electromagnetics Research M, Vol. 53, 29-39, 2017.
doi:10.2528/PIERM16102903

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