基于小波变换与主成分分析的探地雷达自适应杂波抑制方法研究

基金项目:

国家自然科学基金(61372160)和高等学校博士学位点科研专项基金 (20134307110011)资助课题

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

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)

摘要: 针对传统主成分分析法在探地雷达杂波抑制方面的不足，该文基于2维小波变换的分时分频特点，提出了改进的主成分分析子空间投影法。进一步将改进的子空间投影法与自适应横向滤波方法相结合，保留了自适应滤波方法良好的目标回波信号保真度与学习适应能力等优点，提出了基于小波变换与主成分分析的探地雷达自适应杂波抑制方法，实现了小波变换、主成分分析法以及自适应滤波方法的优势互补。实验结果表明该方法在信杂比与目标图像清晰度方面具有良好的杂波抑制效果。
- 探地雷达 /
- 杂波抑制 /
- 主成分分析 /
- 小波变换 /
- 自适应滤波
Abstract: 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.
- Ground Penetrating Radar (GPR) /
- Clutter reduction /
- Principal Component Analysis (PCA) /
- Wavelet transform /
- Adaptive filtering