In order to alleviate the impact of radio frequency interference(RFI)on the accuracy of ocean salinity satellite remote sensing,scholars have proposed various detection and labelingalgorithms for RFI based on remote ...
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In order to alleviate the impact of radio frequency interference(RFI)on the accuracy of ocean salinity satellite remote sensing,scholars have proposed various detection and labelingalgorithms for RFI based on remote sensing data from the SMOS ***,the signals that generate RFI are diverse,and the factors that influence remote sensing observation data are *** algorithms often target specific hypothetical conditions,lacking general applicability,which frequently leads to an important gap between the nominal performance of the literature and practical applications,posing great challenges to data labeling *** address this problem,this study conducted a comprehensive and systematic analysis of RFI simulation based on scene modeling,algorithm modeling,and RFI energy *** typical RFI detectionalgorithms were selected,and the simulation scene was divided into 3 typical scenes:ocean,land,and sea–land scenes,and RFI was analyzed in terms of weak,moderate,strong,and extremely strong based on *** simulation analysis and evaluation of RFI detectionalgorithms,lookup tables for algorithm selection,detection rate,and false-positive rate have been established for different intensities of independent RFI sources and multiple nearby RFI sources in the above *** lookup tables have universal guiding significance and provide reliability assurance in complex situations.
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