Detection and mitigation of RFI in SBRS observation data

Abstract

In view of the inconsistency of channel gains and a large amount of interference noise in Solar Broadband Radio Spectrometer (SBRS) observation data, they will seriously affect the analysis of SBRS data. In this paper, a method of Radio Frequency Interference (RFI) detection and mitigation for SBRS observation data is reported. Firstly, the SBRS observation data are preprocessed, a part of the observation data was selected to calculate the mean and variance to achieve the normalization of the entire observation data, which can avoid the influence of strong noise on the normalization result. Furthermore, we proposed an adaptive threshold RFI detection method based on fusion wavelet transform reconstruction and an RFI elimination method based on neighborhood weighted filling. It is worth mentioning that to detect RFI interference signals of different magnitudes, we adopted an iterative approach to the RFI detection and mitigation process. Through qualitative analysis of real observation data and quantitative analysis of simulated data, it is shown that the method proposed in this paper can effectively eliminate RFI in SBRS observation data, and improve the quality of observation data for further scientific analysis.