Optimization identification algorithm of characteristic parameters of electromagnetic emission elements

It is very difficult to analyze electromagnetic interference in complex electronic information systems because of the wide range of internal and external electromagnetic environment and the complex coupling relationship. Electromagnetic emission can be characterized and analyzed by the theory of electromagnetic emission elements. Harmonics are an important part of many types of electromagnetic emission and can be considered as the key to identify most basic elements of switch class. However, most electromagnetic emission test data are noisy signals, which greatly reduces the accuracy of switch element identification. In this paper, starting from the electromagnetic emission test data, the electromagnetic emission spectrum data is processed in time domain, and then the compressed sensing method is used to improve the signal-to-noise ratio of the data, so as to improve the accuracy of extracting, identifying and characterizing the basic elements of switch class and the parameters in time domain and frequency domain from the test data.