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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JERA</journal-id><journal-title-group><journal-title>Journal of Electronic Research and Application</journal-title></journal-title-group><issn>2208-3502</issn><eissn>2208-3510</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jera.v8i1.6026</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research on Modulation Signal Denoising Method Based on Improved Variational Mode Decomposition</title><url>https://artdesignp.com/journal/JERA/8/1/10.26689/jera.v8i1.6026</url><author>MoCanyu,LinQianqiang,NiuYuanduo,DuHaoran</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>8</volume><issue>1</issue><history><date date-type="pub"><published-time>2024-01-18</published-time></date></history><abstract>In order to further analyze the micro-motion modulation signals generated by rotating components and extractmicro-motion features, a modulation signal denoising algorithm based on improved variational mode decomposition (VMD)is proposed. To improve the time-frequency performance, this method decomposes the data into narrowband signalsand analyzes the internal energy and frequency variations within the signal. Genetic algorithms are used to adaptivelyoptimize the mode number and bandwidth control parameters in the process of VMD. This approach aims to obtain theoptimal parameter combination and perform mode decomposition on the micro-motion modulation signal. The optimalmode number and quadratic penalty factor for VMD are determined. Based on the optimal values of the mode numberand quadratic penalty factor, the original signal is decomposed using VMD, resulting in optimal mode number intrinsicmode function (IMF) components. The effective modes are then reconstructed with the denoised modes, achieving signaldenoising. Through experimental data verification, the proposed algorithm demonstrates effective denoising of modulationsignals. 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