摘要
By applying the state-of-the-art mathematical apparatus, the wavelet transformation, we explore the possibility of a dynamic cleaning of raw data ob- tained with the Chinese solar radio spectrographs over a wide wavelength range (from 0.7 to 7.6 GHz). We consider the problem of eliminating the interference caused by combination rates of data sampling (10-20 ins), and the low-frequency interference (4-30 s) caused by the receiving equipment changing its characteristics with time. It is shown that the best choice to reconstruct a signal suffering from amplitude, frequency and phase instabilities, is by means of wavelet transformation at both high and low frequencies. We analysed observational data which contained interferences of nonsolar origin such as instrumental effects and other man-made signals. A subsequent comparison of the reference data obtained with the acousto- optical receiver of the Siberian Solar Radio Telescope (SSRT) with the 'cleaned' spectra confirms the correctness of this approach.
By applying the state-of-the-art mathematical apparatus, the wavelet transformation, we explore the possibility of a dynamic cleaning of raw data ob- tained with the Chinese solar radio spectrographs over a wide wavelength range (from 0.7 to 7.6 GHz). We consider the problem of eliminating the interference caused by combination rates of data sampling (10-20 ins), and the low-frequency interference (4-30 s) caused by the receiving equipment changing its characteristics with time. It is shown that the best choice to reconstruct a signal suffering from amplitude, frequency and phase instabilities, is by means of wavelet transformation at both high and low frequencies. We analysed observational data which contained interferences of nonsolar origin such as instrumental effects and other man-made signals. A subsequent comparison of the reference data obtained with the acousto- optical receiver of the Siberian Solar Radio Telescope (SSRT) with the 'cleaned' spectra confirms the correctness of this approach.
