① (国防科学技术大学电子科学与工程学院 长沙 410073) ② (解放军工程兵学院 徐州 221000)
Adaptive clutter reduction based on wavelet transform and principal component analysis for ground penetrating radar
Qin Yao①* Huang Chun-lin① Lu Min① Xu Wei②
① (School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China) ② (Engineer Academy of People’s Liberation Army, Xuzhou 221000, China)
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.
2015, Vol. 4 
