Method for Homologous Spectrum Monitoring Data Identification Based on Spectrum SIFT
With the popularity of various radio applications,different kinds of monitoring data in the process of ultra-short wave monitoring is susceptible to the influence of non-homologous signals of the same frequency or adjacent frequency within a limited space.It is impossible to determine whether the signals are homologous or not merely relying on the frequency spectrum data in conventional monitoring,so that the data obtained from different monitoring stations lack of correlation and the data analysis re-sults may be misleading,even affecting work efficiency.Based on the experience of manual monitoring,this paper attempts to ana-lyze the frequency spectrum and time-frequency spectrum with computer vision technology,and introduces angle threshold to im-prove the feature point matching mode of SIFT algorithm in combination with the spectrum characteristics,so as to meet the needs of radio monitoring data analysis.Meanwhile,this paper puts forward a method to comprehensively evaluate the consistency of the homologous determination results of two kinds of spectra by using the Kappa on the premise of the matching rate of image feature point detection.Through experimental simulation and case validation,the Kappa of the homologous result is 0.760 5,which is highly consistent.At last,the proposed methodcan improve work efficiency in practice,and has operational feasibility and practical significance.
Radio monitoringHomologous determinationFeature point matchingImage processingComputer visionScale invariant feature transform
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