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Very low frequency signals (VLF) which are observed by DEMETER satellite is often corrupted by atmospheric and manmade noise. These noises affect the quality of the VLF signal. So for quality improvement denoising of VLF signal is must. The denoising methods which are used for VLF signal often consider noise nature as Gaussian. But the nature of atmospheric and manmade noise is non-gaussian. Due to this fact denoising methods which are considering noise nature as Gaussian is not effective for the denoising of VLF signals. So in the present work we applied a statistical signal processing method for the denoising of noise being non-Gaussian is known as the independent component analysis (ICA) in which signal and noise considered to be independent and non-Gaussian.ICA based preprocesses boost the higher order correlation (bispectrum).This study also shows improvement in the signal to noise ratio (SNR) and visualized the suppressed frequency of VLF signals in the spectrogram.

Study of Very Low Frequency Signal by Independent Component Analysis Observed Form DEMETER Satellite