{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T04:54:23Z","timestamp":1777006463209,"version":"3.51.4"},"reference-count":25,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,7,3]],"date-time":"2022-07-03T00:00:00Z","timestamp":1656806400000},"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":["42076195"],"award-info":[{"award-number":["42076195"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Atmospheric duct parameters inversion is an important aspect of microwave-band radar and communication system performance evaluation. AIS (Automatic Identification System) is one of the signal sources used for atmospheric duct parameters inversion. Before the inversion of atmospheric duct parameters, determining the type of atmospheric duct plays an important role in the inversion results, but the current inversion methods ignore this point. We outlined a classifying-inversion method of atmospheric duct parameters using AIS signals combined with artificial intelligence. The method consists of an atmospheric duct classification model and a parameter inversion model. The classification model judges the type of atmospheric duct, and the inversion model inverts the atmospheric duct parameters according to the type of atmospheric duct. Our findings demonstrated that the accuracy of the atmospheric duct classification model based on deep neural network (DNN) even exceeds 97%, and the atmospheric duct parameters inversion model has better inversion accuracy than that of the traditional method, thereby illustrating the effectiveness and accuracy of this novel method.<\/jats:p>","DOI":"10.3390\/rs14133197","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T20:59:18Z","timestamp":1656968358000},"page":"3197","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["A Classifying-Inversion Method of Offshore Atmospheric Duct Parameters Using AIS Data Based on Artificial Intelligence"],"prefix":"10.3390","volume":"14","author":[{"given":"Jie","family":"Han","sequence":"first","affiliation":[{"name":"School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China"},{"name":"China Research Institute of Radiowave Propagation, Qingdao 266107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaji","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lijun","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Research Institute of Radiowave Propagation, Qingdao 266107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongguang","family":"Wang","sequence":"additional","affiliation":[{"name":"China Research Institute of Radiowave Propagation, Qingdao 266107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinglin","family":"Zhu","sequence":"additional","affiliation":[{"name":"China Research Institute of Radiowave Propagation, Qingdao 266107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Research Institute of Radiowave Propagation, Qingdao 266107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Zhao","sequence":"additional","affiliation":[{"name":"China Research Institute of Radiowave Propagation, Qingdao 266107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shoubao","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Research Institute of Radiowave Propagation, Qingdao 266107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1175\/1520-0450(1997)036<0193:ANMOTO>2.0.CO;2","article-title":"A New Model of the Oceanic Evaporation Duct","volume":"36","author":"Babin","year":"1997","journal-title":"J. Appl. Meteorol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2873","DOI":"10.1109\/TAP.2021.3098582","article-title":"Digital Maps of Atmospheric Refractivity and Atmospheric Ducts Based on a Meteorological Observation Datasets","volume":"70","author":"Hao","year":"2022","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_3","unstructured":"Skolnik, M. (1980). Electrical Engineering Series. Introduction to Radar Systems, McGraw-Hill."},{"key":"ref_4","unstructured":"Anderson, K.D. (1994, January 19\u201322). Tropospheric Refractivity Profiles Inferred from Low Elevation Angle Measurements of Global Positioning System (GPS) Signals. Proceedings of the of AGARD Conference, Propagation Assessment in Coastal Environments, Bremerhaven, Germany."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/S1364-6826(01)00114-6","article-title":"A Technical Description of Atmospheric Sounding by GPS Occultation","volume":"64","author":"Hajj","year":"2002","journal-title":"J. Atmos. Solar-Terr. Phys."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"24435","DOI":"10.1029\/1999JD900766","article-title":"A Novel Approach to Atmospheric Profiling with a Mountain-Based or Airborne GPS Receiver","volume":"104","author":"Zuffada","year":"1999","journal-title":"J. Geophys. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1109\/LGRS.2012.2227294","article-title":"Monitoring the Marine Atmospheric Refractivity Profiles by Ground-Based GPS Occultation","volume":"10","author":"Wang","year":"2013","journal-title":"IEEE Geosci. Remote Sens."},{"key":"ref_8","unstructured":"(2014). Technical Characteristics for an Automatic Identification System Using Time-Division Multiple Access in the VHF Maritime Mobile Frequency Band (Standard No. ITU-R M.1371-5)."},{"key":"ref_9","unstructured":"(2007). Long Range Detection of Automatic Identification System (AIS) Messages Under Various Tropospheric Propagation Conditions (Standard No. ITU-R M.2123)."},{"key":"ref_10","unstructured":"Bruin, E.R. (2016). Modelling the Impact of North Sea Weather Conditions on the Performance of AIS and Coastal Radar Systems. [Master\u2019s Thesis, Utrecht University]."},{"key":"ref_11","unstructured":"Zhang, L.J., Wang, H.G., and Li, J.R. (2022). Experimental Analysis of Low Atmospheric Duct Monitoring Based on AIS Signal. Chin. J. Radio Sci., (In Chinese)."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Gerstoft, P., Rogers, L.T., Krolik, J.L., and Hodgkiss, W.S. (2003). Inversion for Refractivity Parameters from Radar Sea Clutter. Radio Sci., 38.","DOI":"10.1029\/2002RS002640"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2006RS003561","article-title":"Statistical Maritime Radar Duct Estimation Using a Hybrid Genetic Algorithm-Markov Chain Monte Carlo Method","volume":"42","author":"Yardim","year":"2007","journal-title":"Radio Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.scs.2018.09.009","article-title":"Deep Learning for Solving Inversion Problem of Atmospheric Refractivity Estimation","volume":"43","author":"Guo","year":"2018","journal-title":"Sustain. Cities Soc."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Han, J., Wu, J.J., Zhu, Q.L., Wang, H.G., Zhou, Y.F., Jiang, M.B., Zhang, S.B., and Wang, B. (2021). Evaporation Duct Height Nowcasting in China\u2019s Yellow Sea Based on Deep Learning. Remote Sens., 13.","DOI":"10.3390\/rs13081577"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1029\/2019RS006798","article-title":"Characterizing Evaporation Ducts Within the Marine Atmospheric Boundary Layer Using Artificial Neural Networks","volume":"54","author":"Sit","year":"2019","journal-title":"Radio Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Han, J., Wu, J.J., Wang, H.G., Zhu, Q.L., Zhang, L.J., Zhang, C., Wang, Q.N., and Zhao, H. (2022). Weight Loss Function for the Cooperative Inversion of Atmospheric Duct Parameters. Atmosphere, 13.","DOI":"10.3390\/atmos13020338"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.aeue.2017.12.009","article-title":"A Novel Hybrid Model for Inversion Problem of Atmospheric Refractivity Estimation","volume":"84","author":"Tepecik","year":"2018","journal-title":"Int. J. Electron. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"104919","DOI":"10.1016\/j.cageo.2021.104919","article-title":"Deep Learning for Classifying and Characterizing Atmospheric Ducting Within the Maritime Setting","volume":"157","author":"Hs","year":"2021","journal-title":"Comput. Geosci."},{"key":"ref_20","first-page":"996","article-title":"A Study on the Propagation Characteristics of AIS Signals in the Evaporation Duct Environment","volume":"34","author":"Tang","year":"2019","journal-title":"Appl. Comp. Electromagn. Soc. J."},{"key":"ref_21","unstructured":"Liu, C.G. (2003). Research on Evaporation Duct Propagation and Its Applications, Xidian University."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2011RS004818","article-title":"Refractivity Estimation from Sea Clutter: An Invited Review","volume":"46","author":"Karimian","year":"2011","journal-title":"Radio Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1109\/8.8634","article-title":"Modeling Electromagnetic Wave Propagation in the Troposhere Using the Parabolic Equation","volume":"36","author":"Dockery","year":"1988","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Levy, M.F. (2000). Parabolic Equation Methods for Electromagnetic Wave Propagation, The Institution of Electrical Engineers.","DOI":"10.1049\/PBEW045E"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Coley, D.A. (1999). An Introduction to Genetic Algorithms for Scientists and Engineers, World Scientific Publishing.","DOI":"10.1142\/3904"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3197\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:42:21Z","timestamp":1760139741000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3197"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,3]]},"references-count":25,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133197"],"URL":"https:\/\/doi.org\/10.3390\/rs14133197","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,3]]}}}