Auto-selected rule on principal component analysis in ground penetrating radar signal denoising

Jia Quan Shen*, Huai Zhi Yan, Chang Zhen Hu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Since the principal component analysis algorithm has no robust threshold and dependent on artificial selection of the principal components, an auto-selected rule which is composed of two parts is proposed. One is mean cumulated energy percent standard which makes the mean energy as stable threshold value to discard principal component connected with ground bounce wave. The other part is an improved local energy percent ratio rule to discard the principal component related to background signals. The remaining principal components are reconstructed to denoise image to suppress the ground bounce wave and remove background signals. Experimental results show that the rule can solve the problem and the threshold value is more robust than the one of whole energy percent.

Original languageEnglish
Pages (from-to)83-87
Number of pages5
JournalDianbo Kexue Xuebao/Chinese Journal of Radio Science
Volume25
Issue number1
Publication statusPublished - Feb 2010

Keywords

  • Ground penetrating radar
  • Principal component analysis
  • Signal denoising
  • Single value decomposition

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