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

Jichao Zhu | Zendy; Wei Xue | Zendy; Rong Xia | Zendy; Yunyun Yu | Zendy

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

Author(s) -

Jichao Zhu,

Wei Xue,

Rong Xia,

Yunyun Yu

Publication year - 2017

Publication title -

progress in electromagnetics research m

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.216

H-Index - 31

ISSN - 1937-8726

DOI - 10.2528/pierm16102903

Subject(s) - clutter , ground penetrating radar , principal component analysis , selection (genetic algorithm) , radar , computer science , component (thermodynamics) , remote sensing , artificial intelligence , geology , telecommunications , physics , thermodynamics

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.

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