Emission Spectrum and Parameter Identification Method of Nonlinear System with Correlated Source Input

Identifying the frequency of an emitting source in the emission spectrum is an effective method for troubleshooting in electronic systems. However, nonlinear devices in circuits produce complex spectrum, increasing the difficulty of frequency identification. To solve the problem of spectrum identification in nonlinear circuits, a signal identification method based on spectral features is proposed, aiming to analyze the spectral characteristics of typical analog source and digital source intermodulation. Two typical signal combination cases are investigated: one is the sum of sinusoidal signals multiplied by a square wave signal, and the other is the multiplication of two square wave signals. The fundamental frequency of the signal is extracted by analyzing the spectrum modulus value and autocorrelation transformation. The effectiveness and anti-interference capability of the proposed method are verified through simulation analysis and interference analysis.

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Published
2025-05-23
DOI
https://doi.org/10.1109/iwrfat65352.2025.11103125
Primary Topic
Advanced Measurement and Detection Methods
Type
article
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article

Emission Spectrum and Parameter Identification Method of Nonlinear System with Correlated Source Input

Yuan Miao, Ziyao Chen, Hui Xu
Advanced Measurement and Detection Methods
article

Emission Spectrum and Parameter Identification Method of Nonlinear System with Correlated Source Input

Yuan Miao, Ziyao Chen, Hui Xu
article en

Abstract

Identifying the frequency of an emitting source in the emission spectrum is an effective method for troubleshooting in electronic systems. However, nonlinear devices in circuits produce complex spectrum, increasing the difficulty of frequency identification. To solve the problem of spectrum identification in nonlinear circuits, a signal identification method based on spectral features is proposed, aiming to analyze the spectral characteristics of typical analog source and digital source intermodulation. Two typical signal combination cases are investigated: one is the sum of sinusoidal signals multiplied by a square wave signal, and the other is the multiplication of two square wave signals. The fundamental frequency of the signal is extracted by analyzing the spectrum modulus value and autocorrelation transformation. The effectiveness and anti-interference capability of the proposed method are verified through simulation analysis and interference analysis.

MWT Materials (United States) (US), State Key Laboratory of Remote Sensing Science (CN), Beihang University (CN)
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Advanced Measurement and Detection Methods
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