Abnormal electromagnetic monitoring and electromagnetic spectrum data completion method based on original RF I/Q distribution characteristics

The management and control of electromagnetic spectrum resources is a key technology for improving spectrum utilization. Interference in the same frequency band or fluctuations in background noise will affect the spectrum resources of wireless communication and reduce the spectrum utilization rate. The numerical fluctuation range of traditional energy detection methods is relatively small, and their detection ability for weak signals or electromagnetic interference is poor. In order to improve the monitoring ability of electromagnetic spectrum resources, this paper proposes an electromagnetic interference monitoring method based on the distribution characteristics of the original radio frequency I/Q data. This paper proposes a method for detecting abnormal electromagnetic spectrum fluctuations based on the monitoring of cumulative distance parameters of RF I/Q component weights. Detect abnormal electromagnetic fluctuation events based on the changes in the distribution characteristics of radio frequency I/Q. Compared with energy detection methods, the proposed algorithm is less complex and can effectively improve the detection ability of weak electromagnetic interference. In order to enhance the monitoring capability of abnormal electromagnetic spectra, an electromagnetic spectrum data completion method based on quartile distribution characteristics is proposed for the electromagnetic spectrum monitoring system. The average relative error between the sample data that has completed the electromagnetic spectrum data completion and the original monitoring data of the electromagnetic spectrum is less than 0.002. Through the analysis and verification of the measured data of the electromagnetic spectrum, this method can effectively improve the electromagnetic interference detection ability in complex environments.