Research on the Ground Penetrating Radar Clutter Suppression Technology Based on PCA Method

DOI

10.2991/icecee-15.2015.53How to use a DOI?

Keywords

Ground Penetrating Radar; Principal Component Analysis; clutter suppression

Abstract

The reduction of background clutter signal from Ground Penetrating Radar (GPR) experiments is an area of active research. The weak reflection signal obtained from subsurface targets is usually blurred by such strong clutter. Therefore, clutter suppression is the key step in ground penetrating radar signal processing. In this paper, Principal Component Analysis (PCA) algorithm is used to suppress GPR clutter. First, mean filter method is used to remove the direct wave and part of noise signal in the reflection wave, and then the processed observing data are divided into target space and clutter space. After that, signals in target space are decomposed into independent components by dimension reduction. Finally, removing small components can get the purposes of outstanding effective target and clutter suppression. By dealing with GPR experiment data, it shows that the PCA algorithm based on mean filter to suppress clutter is effectiveness and stability.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - DeMei Yang
AU  - Yao Qin
AU  - Xiaozhen Ren
PY  - 2015/06
DA  - 2015/06
TI  - Research on the Ground Penetrating Radar Clutter Suppression Technology Based on PCA Method
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 239
EP  - 242
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.53
DO  - 10.2991/icecee-15.2015.53
ID  - Yang2015/06
ER  -