{"id":"https://openalex.org/W7128682404","doi":"https://doi.org/10.1109/tii.2026.3658808","title":"Improved Data Augmentation and Cross-Modal Feature Fusion for Sonar Target Classification Under Reverberation Background","display_name":"Improved Data Augmentation and Cross-Modal Feature Fusion for Sonar Target Classification Under Reverberation Background","publication_year":2026,"publication_date":"2026-02-12","ids":{"openalex":"https://openalex.org/W7128682404","doi":"https://doi.org/10.1109/tii.2026.3658808"},"language":null,"primary_location":{"id":"doi:10.1109/tii.2026.3658808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2026.3658808","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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/A5121519732","display_name":"Yuqi Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqi Zheng","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0009-0000-7806-0271","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008486784","display_name":"Lerong Hong","orcid":"https://orcid.org/0000-0002-6626-7985"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lerong Hong","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-6626-7985","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125725355","display_name":"Boyu Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyu Zhao","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hongzhuang Cao","orcid":"https://orcid.org/0009-0006-1053-4331"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongzhuang Cao","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0009-0006-1053-4331","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18032061,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"5","first_page":"4468","last_page":"4479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9146999716758728,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9146999716758728,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.02319999970495701,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.01730000041425228,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/sonar","display_name":"Sonar","score":0.8167999982833862},{"id":"https://openalex.org/keywords/reverberation","display_name":"Reverberation","score":0.7264000177383423},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6175000071525574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5735999941825867},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5455999970436096},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5084999799728394},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4528000056743622},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4392000138759613},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.43209999799728394},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.42399999499320984}],"concepts":[{"id":"https://openalex.org/C555745239","wikidata":"https://www.wikidata.org/wiki/Q133220","display_name":"Sonar","level":2,"score":0.8167999982833862},{"id":"https://openalex.org/C95851461","wikidata":"https://www.wikidata.org/wiki/Q468809","display_name":"Reverberation","level":2,"score":0.7264000177383423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7024999856948853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6586999893188477},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6175000071525574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5735999941825867},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5455999970436096},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5084999799728394},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4528000056743622},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4392000138759613},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4221000075340271},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.37299999594688416},{"id":"https://openalex.org/C77246614","wikidata":"https://www.wikidata.org/wiki/Q1409400","display_name":"Gramian matrix","level":3,"score":0.35409998893737793},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32679998874664307},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C137184094","wikidata":"https://www.wikidata.org/wiki/Q6764300","display_name":"Marine mammals and sonar","level":3,"score":0.3222000002861023},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C2778260390","wikidata":"https://www.wikidata.org/wiki/Q15378713","display_name":"Sonar signal processing","level":4,"score":0.3086000084877014},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26820001006126404},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2026.3658808","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2026.3658808","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.865638792514801,"id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G4343311918","display_name":null,"funder_award_id":"52127901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4579262274","display_name":null,"funder_award_id":"52207200","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Effective":[0],"sonar":[1,88,169],"target":[2,69,170],"classification":[3,119,171],"in":[4,87,134,172],"reverberant":[5],"underwater":[6],"environments":[7],"remains":[8],"a":[9,64,73,91,163],"significant":[10],"challenge":[11],"due":[12],"to":[13,45],"limited":[14],"sample":[15,82],"data":[16],"and":[17,41,100,112,149],"complex":[18],"noise":[19],"interference.":[20],"This":[21,60],"article":[22],"presents":[23],"an":[24],"innovative":[25],"approach":[26],"that":[27,76],"combines":[28],"enhanced":[29,52],"Wasserstein":[30],"generative":[31],"adversarial":[32],"network":[33,94],"with":[34,38,53,63],"gradient":[35],"penalty":[36],"(WGAN-GP)":[37],"frequency-domain":[39],"constraints":[40],"cross-modal":[42],"feature":[43,110],"fusion":[44],"address":[46],"these":[47],"challenges.":[48],"The":[49,114],"WGAN-GP":[50],"model,":[51],"spectrum-aware":[54],"loss,":[55],"generates":[56],"high-fidelity":[57],"reverberation":[58],"signals.":[59],"method,":[61],"coupled":[62],"bright":[65],"spot":[66],"model":[67],"for":[68,108,166],"echo":[70],"simulation,":[71],"creates":[72],"robust":[74],"dataset":[75],"alleviates":[77],"the":[78,139,144,159],"issue":[79],"of":[80],"small":[81],"sizes,":[83],"which":[84],"is":[85,106],"critical":[86],"systems.":[89],"Furthermore,":[90],"multimodal":[92],"convolutional":[93],"leveraging":[95],"Gramian":[96],"angular":[97],"field":[98,103],"(GAF)":[99],"Markov":[101],"transition":[102],"(MTF)":[104],"representations":[105],"introduced":[107],"effective":[109],"extraction":[111],"classification.":[113],"proposed":[115,160],"system":[116],"achieves":[117],"superior":[118],"accuracy,":[120],"averaging":[121],"94.8%":[122],"at":[123],"10":[124],"dB":[125],"signal-to-reverberation":[126],"ratio":[127],"(SRR),":[128],"outperforming":[129],"traditional":[130],"models.":[131],"Experimental":[132],"validation":[133],"diverse":[135],"marine":[136],"environments,":[137],"including":[138],"South":[140],"China":[141],"Sea,":[142],"demonstrates":[143],"framework\u2019s":[145],"high":[146],"generalization":[147],"ability":[148],"strong":[150],"performance":[151],"under":[152],"varying":[153],"SRR":[154],"conditions.":[155],"These":[156],"results":[157],"establish":[158],"method":[161],"as":[162],"powerful":[164],"tool":[165],"robust,":[167],"real-time":[168],"challenging":[173],"environments.":[174]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-02-13T00:00:00"}