{"id":"https://openalex.org/W2547373719","doi":"https://doi.org/10.1109/igarss.2016.7729019","title":"A new PolSAR ship detection metric fused by polarimetric similarity and the third eigenvalue of the coherency matrix","display_name":"A new PolSAR ship detection metric fused by polarimetric similarity and the third eigenvalue of the coherency matrix","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2547373719","doi":"https://doi.org/10.1109/igarss.2016.7729019","mag":"2547373719"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2016.7729019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7729019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047760742","display_name":"Yuyang Xi","orcid":"https://orcid.org/0000-0002-7169-3620"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuyang Xi","raw_affiliation_strings":["Department of Applied Physics, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Applied Physics, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115591673","display_name":"Xi Zhang","orcid":"https://orcid.org/0009-0007-1790-5884"},"institutions":[{"id":"https://openalex.org/I4210114556","display_name":"First Institute of Oceanography","ror":"https://ror.org/01y34t753","country_code":"CN","type":"facility","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210114556","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Zhang","raw_affiliation_strings":["State Oceanic Administration, The First Institute of Oceanography, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"State Oceanic Administration, The First Institute of Oceanography, Qingdao, China","institution_ids":["https://openalex.org/I4210114556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079450266","display_name":"Quan Lai","orcid":"https://orcid.org/0000-0002-3044-058X"},"institutions":[{"id":"https://openalex.org/I22046295","display_name":"Inner Mongolia Normal University","ror":"https://ror.org/0497ase59","country_code":"CN","type":"education","lineage":["https://openalex.org/I22046295"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Lai","raw_affiliation_strings":["Inner Mongolian Key Laboratory of Remote Sensing & Geography Information System, Inner Mongolian Normal University, Hohhot, China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolian Key Laboratory of Remote Sensing & Geography Information System, Inner Mongolian Normal University, Hohhot, China","institution_ids":["https://openalex.org/I22046295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317994","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["College of Information Science & Technology, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science & Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026960113","display_name":"Haitao Lang","orcid":"https://orcid.org/0000-0002-4859-1570"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]},{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haitao Lang","raw_affiliation_strings":["Department of Applied Physics, Beijing University of Chemical Technology, Beijing, China","Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT, Nanjing University of Information Science & Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Department of Applied Physics, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]},{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT, Nanjing University of Information Science & Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5047760742"],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":3.0525,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.91905181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"112","last_page":"115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scattering","display_name":"Scattering","score":0.777737021446228},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7328407764434814},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5753997564315796},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.5734624266624451},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.5426803231239319},{"id":"https://openalex.org/keywords/polarimetry","display_name":"Polarimetry","score":0.533366858959198},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5288832187652588},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4766964614391327},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.46740251779556274},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45320677757263184},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.40506511926651},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3541256785392761},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35301730036735535},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3494551181793213},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31540435552597046},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.27129241824150085},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13478422164916992}],"concepts":[{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.777737021446228},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7328407764434814},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5753997564315796},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.5734624266624451},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.5426803231239319},{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.533366858959198},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5288832187652588},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4766964614391327},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.46740251779556274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45320677757263184},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.40506511926651},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3541256785392761},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35301730036735535},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3494551181793213},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31540435552597046},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.27129241824150085},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13478422164916992},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2016.7729019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7729019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8600000143051147,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1891173781","https://openalex.org/W1974024703","https://openalex.org/W1997695298","https://openalex.org/W2007689604","https://openalex.org/W2008412721","https://openalex.org/W2009911920","https://openalex.org/W2019178979","https://openalex.org/W2044215848","https://openalex.org/W2051702052","https://openalex.org/W2135957796","https://openalex.org/W2997879839","https://openalex.org/W6772281235"],"related_works":["https://openalex.org/W2984210207","https://openalex.org/W1957402038","https://openalex.org/W2920925388","https://openalex.org/W2345828693","https://openalex.org/W1976890621","https://openalex.org/W1512245662","https://openalex.org/W2953817828","https://openalex.org/W2075055239","https://openalex.org/W1557960233","https://openalex.org/W1989124937","https://openalex.org/W3013905424","https://openalex.org/W2386635727","https://openalex.org/W3206856504","https://openalex.org/W2012273884","https://openalex.org/W1578836612","https://openalex.org/W2006000998","https://openalex.org/W2050898759","https://openalex.org/W2986317495","https://openalex.org/W2546795174","https://openalex.org/W2741230768"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,145],"address":[4],"the":[5,16,25,30,38,45,56,65,80,95,123,129,138,148,157,162,197],"problem":[6],"of":[7,18,58,131,156],"ship":[8,22,59,120,143,193,203],"detection":[9,204],"in":[10,147],"PolSAR":[11],"image.":[12],"We":[13],"firstly":[14],"investigate":[15],"differences":[17],"scattering":[19,41,57,68,83,140],"mechanism":[20],"between":[21],"targets":[23,60,121],"and":[24,79,133,160],"sea":[26,39,124],"surface":[27,40],"based":[28,195],"on":[29,98,196],"polarimetric":[31],"similarity":[32],"analysis.":[33],"It":[34],"is":[35,42,90],"shown":[36],"that,":[37],"dominated":[43,63],"by":[44,64],"odd":[46],"bounce":[47,67,82],"(denoted":[48],"as":[49],"r":[50,169],"<sub":[51,70,85,104,108,112,152,165,170,174,178],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[52,71,86,105,109,113,153,166,171,175,179],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[53,114,180],"),":[54],"while":[55],"are":[61],"both":[62],"even":[66],"(r":[69,84,103,164],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sub>":[72,106,167],")":[73,88,155],"which":[74,89,136],"has":[75],"been":[76],"widely":[77],"accepted,":[78],"line":[81],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">4</sub>":[87,110,172],"a":[91,101,187],"new":[92],"find":[93],"from":[94,122],"experiments.":[96],"Based":[97],"those":[99],"differences,":[100],"metric":[102,163,199],"+r":[107],")/r":[111],"can":[115,200],"be":[116],"applied":[117],"to":[118],"distinguish":[119],"surface.":[125],"To":[126],"further":[127],"suppress":[128],"effects":[130],"sidelobes":[132],"imaging":[134],"artifacts":[135],"have":[137],"same/similar":[139],"behaviors":[141],"with":[142],"targets,":[144],"introduce":[146],"third":[149],"eigenvalue":[150],"\u03bb":[151],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sub>":[154,176],"coherency":[158],"matrix":[159],"obtain":[161,201],"+":[168],")\u03bb":[173],"/r":[177],".":[181],"The":[182],"preliminary":[183],"results":[184],"show":[185],"that":[186],"constant":[188],"false":[189],"alarm":[190],"rate":[191],"(CFAR)":[192],"detector":[194],"proposed":[198],"promising":[202],"performance.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}