Adaptive clutter reduction based on wavelet transform and principal component analysis for ground penetrating radar

Leida xuebao

Xu Wei¹  Huang Chun-lin²  Lu Min²  Qin Yao² 

[1] Engineer Academy of People’s Liberation Army;School of Electronic Science and Engineering, National University of Defense Technology;

关键词: Ground Penetrating Radar (GPR);    Clutter reduction;    Principal Component Analysis (PCA);    Wavelet transform;    Adaptive filtering;   

DOI  :  10.12000/JR15013

来源: DOAJ

【 摘 要 】

Because of the limitations of traditional Principal Component Analysis (PCA) in clutter reduction, an improved PCA subspace method is proposed based on the 2D wavelet transform. Moreover, the combination of the improved subspace method and adaptive filtering ensures the signal fidelity and learning adaptability of adaptive filtering. Then, an adaptive clutter reduction algorithm based on wavelet transform and PCA, as well as adaptive filtering, is proposed. The experimental results suggest that the proposed method improves the signal to clutter ratio and target image definition.

【 授权许可】

Unknown