Wavelet Analysis And Its Applications To The Processing Of Solar Radio Data Observed

Wavelet analysis is a kind of multi-scale analytical methods. Compared with Fourier and other's time-frequency tools, it has favorable local characteristics in both time and frequency, and it is widely used in signal and image processing.The fine structures of solar radio dynamic spectra involved in this paper can offer metric information, but we can only get noisy data showing reticulate superimposed on the dynamic spectra. From our experiences, the main factor in creation of reticulate lies in the apparatus function of receiving device, usually defined as the apparatus-channel function. Besides, the noise harmonics is also an important interference factor, which present the vertical components of reticulate.For the purpose of determining the fine structures and deleting interferences in solar radio spectra, we introduce a data processing method with the combination of wavelet transform and channel-modification. Firstly, the original data were divided by the each mean value at each channel, which can clean a large part of horizontal branch of grid-texture on spectrum. Secondly, wavelet transform was applied to the result by the first step. And then the signal was reconstructed from its wavelet transform coefficients. As a result, we can clean grid-texture and delete interferences imposed on spectra, and also enhance the display of spectrum. In the last, we also introduced the conception of wavelet spectrum and design a denoising method based on it.