{"id":"https://openalex.org/W4206763478","doi":"https://doi.org/10.1109/tgrs.2021.3138488","title":"A Method for Detecting Small Targets in Sea Surface Based on Singular Spectrum Analysis","display_name":"A Method for Detecting Small Targets in Sea Surface Based on Singular Spectrum Analysis","publication_year":2021,"publication_date":"2021-12-24","ids":{"openalex":"https://openalex.org/W4206763478","doi":"https://doi.org/10.1109/tgrs.2021.3138488"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3138488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3138488","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5081865145","display_name":"Xijie Wu","orcid":"https://orcid.org/0000-0001-5453-5244"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xijie Wu","raw_affiliation_strings":["Naval Aviation University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0001-5453-5244","affiliations":[{"raw_affiliation_string":"Naval Aviation University, Yantai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005014452","display_name":"Hao Ding","orcid":"https://orcid.org/0000-0001-5255-0184"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Ding","raw_affiliation_strings":["Naval Aviation University, Yantai, China"],"raw_orcid":"https://orcid.org/0000-0001-5255-0184","affiliations":[{"raw_affiliation_string":"Naval Aviation University, Yantai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089984086","display_name":"Ningbo Liu","orcid":"https://orcid.org/0000-0001-6166-2946"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ning-Bo Liu","raw_affiliation_strings":["Naval Aviation University, Yantai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Naval Aviation University, Yantai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100635940","display_name":"Jian Guan","orcid":"https://orcid.org/0000-0002-1913-1460"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Guan","raw_affiliation_strings":["Naval Aviation University, Yantai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Naval Aviation University, Yantai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.014,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.98450599,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9973000288009644,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9973000288009644,"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":0.9941999912261963,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.8268038034439087},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6925575137138367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5583763718605042},{"id":"https://openalex.org/keywords/convex-hull","display_name":"Convex hull","score":0.5385867357254028},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5168591141700745},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.48573189973831177},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.47133541107177734},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46623843908309937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44551610946655273},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4442833960056305},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4253045320510864},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4188506007194519},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.41181594133377075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35863709449768066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3292657732963562},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.17473763227462769},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1405215859413147},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.11593899130821228},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.09848052263259888}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.8268038034439087},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6925575137138367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5583763718605042},{"id":"https://openalex.org/C206194317","wikidata":"https://www.wikidata.org/wiki/Q1138624","display_name":"Convex hull","level":3,"score":0.5385867357254028},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5168591141700745},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.48573189973831177},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.47133541107177734},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46623843908309937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44551610946655273},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4442833960056305},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4253045320510864},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4188506007194519},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.41181594133377075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35863709449768066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3292657732963562},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.17473763227462769},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1405215859413147},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.11593899130821228},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.09848052263259888},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3138488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3138488","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[{"id":"https://openalex.org/G2981463836","display_name":"\u6742\u6ce2\u80cc\u666f\u4e0b\u9891\u63a7\u9635MIMO\u96f7\u8fbe\u76ee\u6807\u7a7a\u8ddd\u9891\u805a\u7126\u8ba4\u77e5\u63a2\u6d4b\u6280\u672f\u7814\u7a76","funder_award_id":"61871391","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3432909135","display_name":null,"funder_award_id":"2020M673690","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5640477920","display_name":null,"funder_award_id":"62101583","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6834322865","display_name":null,"funder_award_id":"61871392","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1515031947","https://openalex.org/W1983834069","https://openalex.org/W1984677318","https://openalex.org/W2011363315","https://openalex.org/W2020105744","https://openalex.org/W2064220837","https://openalex.org/W2131439016","https://openalex.org/W2140466611","https://openalex.org/W2159022845","https://openalex.org/W2383731381","https://openalex.org/W2531165854","https://openalex.org/W2579103735","https://openalex.org/W2745787592","https://openalex.org/W2756373030","https://openalex.org/W2805777666","https://openalex.org/W2939093492","https://openalex.org/W2944664740","https://openalex.org/W2980112905","https://openalex.org/W2998102618","https://openalex.org/W3045521046","https://openalex.org/W3110683067","https://openalex.org/W3116525535","https://openalex.org/W4232046536","https://openalex.org/W4378710641","https://openalex.org/W4405928703","https://openalex.org/W6630800495","https://openalex.org/W6786768871","https://openalex.org/W6788180020","https://openalex.org/W6853424926","https://openalex.org/W6875619956"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W1679012645","https://openalex.org/W2070318884","https://openalex.org/W2011939812","https://openalex.org/W1977371217","https://openalex.org/W1480629002"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,14,33,53,65,104,113,128,136,145,162,166,171,176,195,199],"technical":[3],"difficulty":[4],"of":[5,35,55,79,87,95,103,112,116,131,138,178,189,198,207],"marine":[6],"radar":[7,40,56],"to":[8,71],"detect":[9],"small":[10,46],"targets":[11],"embedded":[12],"in":[13,41,110,155],"sea":[15,117,132],"clutter,":[16],"this":[17,50,159],"article":[18],"proposed":[19,200],"a":[20,120],"three-feature":[21],"fusion":[22],"detection":[23,140,152,196],"method":[24,51,68],"based":[25,126],"on":[26,127],"singular":[27,82,89,97,101],"spectrum":[28],"analysis.":[29],"First,":[30],"considering":[31],"that":[32,77,188,206],"number":[34],"coherent":[36],"pulses":[37],"used":[38],"by":[39,143],"scanning":[42],"mode":[43],"is":[44,141,153,185,202],"usually":[45],"(64":[47],"or":[48],"less),":[49],"combines":[52],"application":[54],"historical":[57],"scan":[58],"data":[59,169],"and":[60,73,92,150,216],"current":[61],"frame":[62],"data,":[63],"transfers":[64],"feature":[66,156],"extraction":[67],"from":[69,100],"intraframe":[70],"interframe,":[72],"extracts":[74],"three":[75],"features":[76],"consist":[78],"cumulative":[80],"major":[81],"value":[83],"(CMSV),":[84],"linear":[85,93],"degree":[86,94],"second":[88],"vector":[90,98],"(LDSSV),":[91],"third":[96],"(LDTSV)":[99],"space":[102,157],"cell":[105],"under":[106,135],"test":[107],"(CUT).":[108],"Second,":[109],"view":[111],"unideal":[114],"distribution":[115],"clutter":[118,133],"samples,":[119],"3-D":[121],"concave":[122,181],"hull":[123,148,182,191],"learning":[124,183,192],"algorithm":[125,184],"geometry":[129],"shape":[130],"samples":[134],"framework":[137],"anomaly":[139],"developed":[142],"improving":[144],"original":[146],"convex":[147,190],"algorithm,":[149],"target":[151],"realized":[154],"using":[158,180],"algorithm.":[160],"Under":[161],"same":[163],"parameter":[164],"condition,":[165],"measured":[167],"CSIR":[168],"verify":[170],"two":[172],"following":[173],"points:":[174],"first,":[175],"performance":[177,197],"detector":[179,201],"better":[186,204],"than":[187,205],"algorithm;":[193],"second,":[194],"obviously":[203],"tri-time\u2013frequency":[208],"(TF)-feature":[209],"detector,":[210,212,215],"trifeature-based":[211],"consistency":[213],"factor":[214],"fractal-based":[217],"detector.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
