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Application of wavelet‐based denoising techniques to remote sensing very low frequency signals
Author(s) -
Güzel Esat,
Canyılmaz Murat,
Türk Mustafa
Publication year - 2011
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1029/2010rs004449
Subject(s) - wavelet , thresholding , computer science , noise reduction , selection (genetic algorithm) , pattern recognition (psychology) , artificial intelligence , acoustics , mathematics , telecommunications , physics , image (mathematics)
In this paper, we apply wavelet‐based denoising techniques to experimental remote sensing very low frequency (VLF) signals obtained from the Holographic Array for Ionospheric/Lightning research system and the Elazig VLF receiver system. The wavelet‐based denoising techniques are tested by soft, hard, hyperbolic and nonnegative garrote wavelet thresholding with the threshold selection rule based on Stein's unbiased estimate of risk, the fixed form threshold, the mixed threshold selection rule and the minimax‐performance threshold selection rule. The aim of this study is to find out the direct (early/fast) and indirect (lightning‐induced electron precipitation) effects of lightning in noisy VLF transmitter signals without discomposing the nature of signal. The appropriate results are obtained by fixed form threshold selection rule with soft thresholding using Symlet wavelet family.