{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T13:58:21Z","timestamp":1772114301319,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T00:00:00Z","timestamp":1689897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Strengthening Project of Military Science and Technology Commission","award":["2019-JCJQ-ZD-324"],"award-info":[{"award-number":["2019-JCJQ-ZD-324"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Aiming at the problem of mutual interference between millimeter-wave frequency-modulation continuous-wave (FMCW) radars, an interference mitigation method based on outlier detection and variational mode decomposition (VMD) is proposed in this paper. Firstly, by differential processing of the raw millimeter-wave FMCW radar data, combined with threshold detection, the interfered sample area is located. Adaptive amplitude limiting is applied to the interfered samples to achieve initial suppression of the interference. Then, based on the VMD algorithm, the processed data are adaptively decomposed to obtain multiple intrinsic mode functions (IMFs). The Pearson correlation coefficient between each IMF and the signal before decomposition is calculated, and the IMF with the maximum Pearson correlation coefficient is extracted as the signal component to achieve the separation of the target signal from the interference and noise. The proposed method was validated based on simulation and experimental data. The results show that the proposed method achieves the best performance in terms of signal-to-interference-plus-noise ratio (SINR), mean square error (MSE), and kurtosis in frequency (KF) compared with empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and complete ensemble empirical mode decomposition (CEEMD). Further comparison was made with two typical methods, and the Range\u2013Doppler (RD) map and SINR results showed that the proposed method exhibited certain performance advantages.<\/jats:p>","DOI":"10.3390\/rs15143654","type":"journal-article","created":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T01:12:28Z","timestamp":1690161148000},"page":"3654","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Interference Mitigation Method for Millimeter-Wave Frequency-Modulation Continuous-Wave Radar Based on Outlier Detection and Variational Modal Decomposition"],"prefix":"10.3390","volume":"15","author":[{"given":"Wen","family":"Zhou","sequence":"first","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6448-4839","authenticated-orcid":false,"given":"Xinhong","family":"Hao","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Yang","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lefan","family":"Duan","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiuyan","family":"Yang","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianqiu","family":"Wang","sequence":"additional","affiliation":[{"name":"Science and Technology on Electromechanical Dynamic Control Laboratory, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/MSP.2020.2969319","article-title":"Radar Interference Mitigation for Automated Driving: Exploring Proactive Strategies","volume":"37","author":"Aydogdu","year":"2020","journal-title":"IEEE Signal Process. 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