{"id":"https://openalex.org/W7151019721","doi":"https://doi.org/10.1109/taes.2026.3680886","title":"A Semisupervised Learning Method Robust to Label Noise for Radar Target Recognition Via Label Correction and Sample Selection","display_name":"A Semisupervised Learning Method Robust to Label Noise for Radar Target Recognition Via Label Correction and Sample Selection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7151019721","doi":"https://doi.org/10.1109/taes.2026.3680886"},"language":null,"primary_location":{"id":"doi:10.1109/taes.2026.3680886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2026.3680886","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic Systems","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/A5084106192","display_name":"Haoqi Mei","orcid":"https://orcid.org/0009-0004-9222-1843"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoqi Mei","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0003-1292-3056","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuai Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Guo","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Penghui Wang","orcid":"https://orcid.org/0000-0001-9659-5608"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Penghui Wang","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-9659-5608","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133004527","display_name":"Jun Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Ding","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133006035","display_name":"Wenchao Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenchao Chen","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-8875-1161","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Junkun Yan","orcid":"https://orcid.org/0000-0002-3828-6812"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junkun Yan","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-3828-6812","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hongwei Liu","orcid":"https://orcid.org/0000-0003-4046-163X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Liu","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-4046-163X","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42432846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"62","issue":null,"first_page":"9283","last_page":"9300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.19949999451637268,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.19949999451637268,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.0729999989271164,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.04390000179409981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5727999806404114},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.5547000169754028},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5454000234603882},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5271999835968018},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5120999813079834},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.4643000066280365},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4142000079154968},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.35929998755455017},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.3544999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6998000144958496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6263999938964844},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5727999806404114},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.5547000169754028},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5454000234603882},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5271999835968018},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5120999813079834},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.4643000066280365},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3734999895095825},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34689998626708984},{"id":"https://openalex.org/C147345108","wikidata":"https://www.wikidata.org/wiki/Q6693040","display_name":"Low probability of intercept radar","level":5,"score":0.3411000072956085},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3278000056743622},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.32440000772476196},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.31189998984336853},{"id":"https://openalex.org/C2779726219","wikidata":"https://www.wikidata.org/wiki/Q7685884","display_name":"Target acquisition","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.3075000047683716},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C173028925","wikidata":"https://www.wikidata.org/wiki/Q7831461","display_name":"Track-before-detect","level":4,"score":0.28690001368522644},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C139931591","wikidata":"https://www.wikidata.org/wiki/Q1029151","display_name":"Pulse-Doppler radar","level":4,"score":0.27469998598098755},{"id":"https://openalex.org/C2987759513","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar signal processing","level":4,"score":0.27149999141693115},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2026.3680886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2026.3680886","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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 Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4410281777381897}],"awards":[],"funders":[{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Supervised":[0],"deep":[1],"learning":[2,72,148],"techniques":[3],"have":[4],"been":[5],"widely":[6],"applied":[7],"to":[8,41,52,120],"radar":[9,185],"high-resolution":[10],"range":[11],"profile":[12],"(HRRP)":[13],"target":[14],"recognition,":[15],"achieving":[16],"significant":[17],"improvements":[18],"in":[19,38,192],"classification":[20],"accuracy.":[21],"However,":[22],"these":[23],"methods":[24],"generally":[25],"rely":[26],"on":[27,183],"the":[28,42,108,146,178,188],"assumption":[29],"of":[30,44,89,190],"accurate":[31],"labels,":[32,55],"which":[33,101],"often":[34],"does":[35],"not":[36],"hold":[37],"practice":[39],"due":[40],"prevalence":[43],"label":[45,77,96,199],"noise.":[46],"Label":[47],"noise":[48,200],"can":[49],"cause":[50],"models":[51],"overfit":[53],"incorrect":[54],"thereby":[56],"degrading":[57],"performance":[58,196],"and":[59,143,169,202],"limiting":[60],"practical":[61,203],"deployment.":[62],"To":[63,176],"mitigate":[64],"this":[65],"challenge,":[66],"we":[67],"propose":[68],"UCJS-SSL,":[69],"a":[70,113,151],"semi-supervised":[71,153],"approach":[73,154],"that":[74],"combines":[75],"uncertainty-guided":[76],"correction":[78,97],"with":[79],"Jensen\u2013Shannon":[80],"Divergence":[81],"(JSD)-based":[82],"sample":[83,115],"selection.":[84],"The":[85],"proposed":[86,179],"framework":[87],"consists":[88],"three":[90],"main":[91],"stages.":[92],"First,":[93],"an":[94],"uncertainty-based":[95],"module":[98],"is":[99,118,160],"proposed,":[100],"rectifies":[102],"potentially":[103],"mislabeled":[104],"samples":[105,124,129,171],"by":[106],"leveraging":[107,166],"model's":[109],"predictive":[110],"uncertainty.":[111],"Next,":[112],"JSD-based":[114],"selection":[116],"mechanism":[117],"employed":[119],"reliably":[121],"separate":[122],"clean":[123],"from":[125],"noisy":[126,136],"ones.":[127],"Clean":[128],"are":[130,138],"used":[131],"for":[132,162,172],"supervised":[133],"learning,":[134],"whereas":[135],"ones":[137],"treated":[139],"as":[140],"unlabeled":[141,170],"data":[142,186],"incorporated":[144],"into":[145],"unsupervised":[147],"process.":[149],"Finally,":[150],"tailored":[152],"termed":[155],"Consistency-Enhanced":[156],"Averaged":[157],"Match":[158],"(CEA-Match)":[159],"designed":[161],"HRRP":[163],"data,":[164],"effectively":[165],"both":[167],"labeled":[168],"robust":[173],"model":[174],"training.":[175],"verify":[177],"approach,":[180],"experimental":[181],"results":[182],"real-world":[184],"validate":[187],"effectiveness":[189],"UCJS-SSL":[191],"maintaining":[193],"high":[194],"recognition":[195],"across":[197],"varying":[198],"levels":[201],"scenarios.":[204]},"counts_by_year":[],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2026-04-07T00:00:00"}