Research on interference and noise reduction technology of solar radio observation system

Abstract

The dynamic spectrum of solar radio burst is a very important tool to study the characteristics of solar radio burst. However, due to the influence of the instruments noise of the solar radio telescope, external interference, the change of ambient temperature, absorption of clouds and so on, the sensitivity of the observation system will be reduced. In particular, the weak solar radio burst signal is easily submerged by various interference signals. In order to improve the sensitivity of solar radio telescope to observe solar radio burst signals and remove narrow-band interference signals, a spectrum data processing algorithm of spectral subtraction method based on entropy and energy threshold values (SSM-EE) is proposed in this article. There are multiple processing steps of SSM-EE. The first step is to improve the signal-to-noise ratio (SNR) through accumulating and averaging the spectrum data. The second step is to eliminate narrowband interference. The spectral kurtosis algorithm is used to calculate the spectral kurtosis of the narrowband interference signal, and then whether to smooth it is determined according to whether it is greater than the threshold. The third step is to establish a noise model. Calculating the power spectrum entropy and energy entropy of each frame of the processed spectrum data, judge whether it is a noise signal by judging the relationship between the power spectrum entropy and energy entropy and the corresponding threshold. The update model for noise floor is used to obtain the real-time noise floor data. The last step is to eliminate the background noise through spectral subtraction. The new spectrum data are obtained by subtraction method between the original spectrum data and the noise floor data. After a large number of data simulation and verification of the actual observation data, it shows that the method proposed in this article has good practical value.