{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T16:16:08Z","timestamp":1775060168880,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,10]],"date-time":"2019-01-10T00:00:00Z","timestamp":1547078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61875089"],"award-info":[{"award-number":["61875089"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11374161"],"award-info":[{"award-number":["11374161"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Primary Research &amp; Development Plan of Jiangsu Province, China","award":["BE2016756"],"award-info":[{"award-number":["BE2016756"]}]},{"name":"Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China","award":["1081080015001"],"award-info":[{"award-number":["1081080015001"]}]},{"name":"Top-notch Academic Programs Project of Jiangsu Higher Education Institutions, China","award":["1181081501003"],"award-info":[{"award-number":["1181081501003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Although lidar is a powerful active remote sensing technology, lidar echo signals are easily contaminated by noise, particularly in strong background light, which severely affects the retrieval accuracy and the effective detection range of the lidar system. In this study, a coupled variational mode decomposition (VMD) and whale optimization algorithm (WOA) for noise reduction in lidar signals is proposed and demonstrated completely. The combination of optimal VMD parameters of decomposition mode number K and quadratic penalty \u03b1 was obtained by using the WOA and was critical in acquiring satisfactory analysis results for VMD denoising technology. Then, the Bhattacharyya distance was applied to identify the relevant modes, which were reconstructed to achieve noise filtering. Simulation results show that the performance of the proposed VMD-WOA method is superior to that of wavelet transform, empirical mode decomposition, and its variations. Experimentally, this method was successfully used to filter a lidar echo signal. The signal-to-noise ratio of the denoised signal was increased to 23.92 dB, and the detection range was extended from 6 to 10 km.<\/jats:p>","DOI":"10.3390\/rs11020126","type":"journal-article","created":{"date-parts":[[2019,1,11]],"date-time":"2019-01-11T04:10:16Z","timestamp":1547179816000},"page":"126","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Efficient Lidar Signal Denoising Algorithm Using Variational Mode Decomposition Combined with a Whale Optimization Algorithm"],"prefix":"10.3390","volume":"11","author":[{"given":"Hongxu","family":"Li","sequence":"first","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"},{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"given":"Jianhua","family":"Chang","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"},{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"given":"Fan","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3685-3825","authenticated-orcid":false,"given":"Zhenxing","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"},{"name":"Department of Information Technology, Taizhou Polytechnic College, Taizhou 225300, Jiangsu, China"}]},{"given":"Zhenbo","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"given":"Luyao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"given":"Shuyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"given":"Renxiang","family":"Mao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"given":"Xiaolei","family":"Dou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]},{"given":"Binggang","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Nanjing University of Information Science &amp; Technology, Nanjing 210044, Jiangsu, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/s11082-011-9503-6","article-title":"Noise reduction for lidar returns using local threshold wavelet analysis","volume":"43","author":"Mao","year":"2012","journal-title":"Opt. 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