{"id":"https://openalex.org/W4415399623","doi":"https://doi.org/10.1109/spml66318.2025.11199780","title":"Ship and Corner Reflector Recognition Based on SAR Images","display_name":"Ship and Corner Reflector Recognition Based on SAR Images","publication_year":2025,"publication_date":"2025-07-15","ids":{"openalex":"https://openalex.org/W4415399623","doi":"https://doi.org/10.1109/spml66318.2025.11199780"},"language":null,"primary_location":{"id":"doi:10.1109/spml66318.2025.11199780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spml66318.2025.11199780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 8th International Conference on Signal Processing and Machine Learning (SPML)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100409861","display_name":"Jian Zhang","orcid":"https://orcid.org/0000-0001-5764-9351"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023441908","display_name":"Shanhong Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanhong Guo","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005833837","display_name":"Shulai Wang","orcid":"https://orcid.org/0000-0002-9760-1050"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shulai Wang","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101867966","display_name":"Shuai Liu","orcid":"https://orcid.org/0000-0001-8261-3086"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Liu","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22","last_page":"27"},"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":0.7843999862670898,"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":0.7843999862670898,"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":0.7728000283241272,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.6747999787330627,"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/corner-reflector","display_name":"Corner reflector","score":0.7831000089645386},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.541100025177002},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.46399998664855957},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.392300009727478},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.3856000006198883},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.3788999915122986},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.36649999022483826},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.365200012922287},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.35659998655319214}],"concepts":[{"id":"https://openalex.org/C117818321","wikidata":"https://www.wikidata.org/wiki/Q1249999","display_name":"Corner reflector","level":2,"score":0.7831000089645386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6067000031471252},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.541100025177002},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5177000164985657},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49309998750686646},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.46399998664855957},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3799999952316284},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.3788999915122986},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.365200012922287},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C3019883945","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Low resolution","level":3,"score":0.30880001187324524},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.28040000796318054},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2768999934196472},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C39499422","wikidata":"https://www.wikidata.org/wiki/Q697320","display_name":"Corner detection","level":3,"score":0.2705000042915344},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.2662999927997589},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.2567000091075897},{"id":"https://openalex.org/C133848361","wikidata":"https://www.wikidata.org/wiki/Q4764027","display_name":"Angular resolution (graph drawing)","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C2778415886","wikidata":"https://www.wikidata.org/wiki/Q1823435","display_name":"Reflector (photography)","level":3,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spml66318.2025.11199780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spml66318.2025.11199780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 8th International Conference on Signal Processing and Machine Learning (SPML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,147],"the":[1,11,29,32,56,65,69,76,82,85,91,97,100,115,120,142,153,171,204,213,219],"modern":[2],"sea":[3],"battlefield,":[4],"enemy":[5,46],"corner":[6,21,86,186],"reflectors":[7,137,187],"can":[8,54,72],"seriously":[9],"affect":[10],"detection":[12],"and":[13,43,84,99,135,144,165,185,207,216],"identification":[14],"capabilities":[15],"of":[16,31,81,133,155,158],"our":[17,39],"radar":[18,40],"systems.":[19],"The":[20,48],"reflector,":[22],"through":[23],"its":[24],"unique":[25],"geometry,":[26],"greatly":[27],"enhances":[28],"strength":[30],"radar's":[33],"echo,":[34],"making":[35],"it":[36,106],"impossible":[37],"for":[38,67,183,223],"to":[41,90,109,119,138,149,200,209],"accurately":[42],"efficiently":[44],"detect":[45],"ships.":[47],"high":[49,77,162],"resolution":[50,78],"range":[51,79],"profile":[52,80],"(HRRP)":[53],"distinguish":[55,110],"difference":[57,93],"in":[58,94,122,126,141,203,212],"distance":[59,143],"between":[60,96,111],"different":[61,104,112],"scattering":[62],"centers":[63],"on":[64,189,231],"target,":[66],"which":[68,197,225],"ship":[70,83,98],"target":[71,123],"be":[73],"identified":[74],"by":[75,170],"reflector.":[87],"However,":[88],"due":[89],"large":[92],"HRRP":[95],"angular":[101,136],"reflector":[102],"at":[103],"angles,":[105],"is":[107,117],"difficult":[108],"targets":[113],"when":[114],"angle":[116],"sensitive":[118],"change":[121],"identification.":[124],"Therefore,":[125],"this":[127,176],"paper,":[128],"we":[129],"construct":[130],"SAR":[131],"images":[132],"ships":[134,184],"recognize":[139],"them":[140],"direction":[145,206],"dimensions.":[146],"order":[148],"better":[150],"deal":[151],"with":[152],"problems":[154],"insufficient":[156],"utilization":[157],"image":[159],"structure":[160],"information,":[161],"computational":[163],"complexity":[164],"small":[166],"samples":[167],"brought":[168],"about":[169],"one-dimensional":[172],"dimensionality":[173],"reduction":[174],"method,":[175],"paper":[177],"proposes":[178],"an":[179],"improved":[180],"recognition":[181,229],"algorithm":[182],"based":[188],"two-dimensional":[190],"two":[191],"dimensional":[192],"two-way":[193],"locally":[194],"maintained":[195],"projection,":[196],"uses":[198,218],"2DLDA+2DLPP":[199],"extract":[201,210],"features":[202,211],"column":[205],"2DPCA+2DLPP":[208],"row":[214],"direction,":[215],"finally":[217],"nearest":[220],"neighbor":[221],"classifier":[222],"classification,":[224],"has":[226],"a":[227,232],"good":[228],"effect":[230],"given":[233],"dataset.":[234]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-22T00:00:00"}