{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:38:15Z","timestamp":1760240295762,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,4,30]],"date-time":"2019-04-30T00:00:00Z","timestamp":1556582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The cross-spectral correlation approach has been used to estimate the wave spectrum from optical and radar images. This work aims to improve the cross-spectral approach to derive current velocity from the X-band marine radar image sequence, and evaluate the application conditions of the method. To reduce the dependency of gray levels on range and azimuth, radar images are preprocessed by the contrast-limited adaptive histogram equalization. Two-dimensional cross-spectral coherence and phase are derived from neighboring X-band marine radar images, and the phases with large coherences are used to estimate the phase velocity and angular frequency of waves, which are first fitted with the theoretical dispersion relation by different least square models, and then the current velocity can be determined. Compared with the current velocities measured by a current meter, the root-mean-square error, correlation coefficient, bias, and relative error are 0.15 m\/s. 0.88, \u20130.05 m\/s, and 7.79% for the north-south velocity, and 0.14 m\/s, 0.86, 0.06 m\/s, and 10.75% for the east-west velocity in the experimental area, respectively. The preprocessing, critical coherence, and the number of images for applying the cross-spectral approach, are discussed.<\/jats:p>","DOI":"10.3390\/rs11091031","type":"journal-article","created":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T03:15:22Z","timestamp":1556766922000},"page":"1031","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Estimation of Sea Surface Current from X-Band Marine Radar Images by Cross-Spectrum Analysis"],"prefix":"10.3390","volume":"11","author":[{"given":"Zhongbiao","family":"Chen","sequence":"first","affiliation":[{"name":"School of Marine Sciences, Jiangsu Engineering Technology Research Center of Marine Environment Detection, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6569-1998","authenticated-orcid":false,"given":"Biao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Marine Sciences, Jiangsu Engineering Technology Research Center of Marine Environment Detection, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"given":"Vladimir","family":"Kudryavtsev","sequence":"additional","affiliation":[{"name":"Satellite Oceanography Laboratory, Russian State Hydrometeorological University, St. Petersburg 195196, Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1531-5262","authenticated-orcid":false,"given":"Yijun","family":"He","sequence":"additional","affiliation":[{"name":"School of Marine Sciences, Jiangsu Engineering Technology Research Center of Marine Environment Detection, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"given":"Xiaoqing","family":"Chu","sequence":"additional","affiliation":[{"name":"South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1826","DOI":"10.1175\/JTECH-D-13-00198.1","article-title":"Measuring turbulent dissipation using a tethered ADCP","volume":"31","author":"Lucas","year":"2014","journal-title":"J. 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