{"id":"https://openalex.org/W7154403397","doi":"https://doi.org/10.1016/j.dsp.2026.106039","title":"Data augmentation for DOA estimation using Wasserstein GAN with gradient penalty","display_name":"Data augmentation for DOA estimation using Wasserstein GAN with gradient penalty","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154403397","doi":"https://doi.org/10.1016/j.dsp.2026.106039"},"language":"en","primary_location":{"id":"doi:10.1016/j.dsp.2026.106039","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.dsp.2026.106039","pdf_url":null,"source":{"id":"https://openalex.org/S64117906","display_name":"Digital Signal Processing","issn_l":"1051-2004","issn":["1051-2004","1095-4333"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Digital Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.dsp.2026.106039","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133595337","display_name":"Zhenshan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenshan Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133581219","display_name":"Wenjie Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Xu","raw_affiliation_strings":["School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133581757","display_name":"Haitao Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haitao Zou","raw_affiliation_strings":["School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123790614","display_name":"Shichao Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091949","display_name":"Shanghai Shipbuilding Technology Research Institute","ror":"https://ror.org/00g2kbc16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210091949"]},{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shichao Yi","raw_affiliation_strings":["School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China","School of Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China","Yangzijiang Shipbuilding Group, Taizhou, 212299, Jiangsu Province, China","Zhenjiang Jizhi Ship Technology Co., Ltd., Zhenjiang, 212003, Jiangsu Province, China"],"raw_orcid":"https://orcid.org/0000-0003-4492-3678","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China","institution_ids":["https://openalex.org/I4210096899"]},{"raw_affiliation_string":"School of Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, Jiangsu Province, China","institution_ids":["https://openalex.org/I4210096899"]},{"raw_affiliation_string":"Yangzijiang Shipbuilding Group, Taizhou, 212299, Jiangsu Province, China","institution_ids":["https://openalex.org/I4210091949"]},{"raw_affiliation_string":"Zhenjiang Jizhi Ship Technology Co., Ltd., Zhenjiang, 212003, Jiangsu Province, China","institution_ids":["https://openalex.org/I4210096899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5123790614"],"corresponding_institution_ids":["https://openalex.org/I4210091949","https://openalex.org/I4210096899"],"apc_list":{"value":2480,"currency":"USD","value_usd":2480},"apc_paid":{"value":2480,"currency":"USD","value_usd":2480},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"179","issue":null,"first_page":"106039","last_page":"106039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.15600000321865082,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.15600000321865082,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.08649999648332596,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.05380000174045563,"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/gradient-method","display_name":"Gradient method","score":0.43320000171661377},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.3278999924659729},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.26750001311302185},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.2597000002861023}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5493000149726868},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5263000130653381},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.43320000171661377},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41749998927116394},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3856000006198883},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28439998626708984},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C6180225","wikidata":"https://www.wikidata.org/wiki/Q3411771","display_name":"Penalty method","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.dsp.2026.106039","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.dsp.2026.106039","pdf_url":null,"source":{"id":"https://openalex.org/S64117906","display_name":"Digital Signal Processing","issn_l":"1051-2004","issn":["1051-2004","1095-4333"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Digital Signal Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.dsp.2026.106039","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.dsp.2026.106039","pdf_url":null,"source":{"id":"https://openalex.org/S64117906","display_name":"Digital Signal Processing","issn_l":"1051-2004","issn":["1051-2004","1095-4333"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Digital Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6455792188644409,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W3080716055","https://openalex.org/W4309347832","https://openalex.org/W4322730826","https://openalex.org/W4360584650","https://openalex.org/W4381460216","https://openalex.org/W4386137735","https://openalex.org/W4387058584","https://openalex.org/W4388419491","https://openalex.org/W4390972457","https://openalex.org/W4396909776","https://openalex.org/W4402417635","https://openalex.org/W4402991010","https://openalex.org/W4404646014","https://openalex.org/W4404726599","https://openalex.org/W4405017620","https://openalex.org/W4405301931","https://openalex.org/W4405912400","https://openalex.org/W4405945247","https://openalex.org/W4405999096","https://openalex.org/W4406373594","https://openalex.org/W4406480963","https://openalex.org/W4406971013","https://openalex.org/W4407510740","https://openalex.org/W4407559406","https://openalex.org/W4407576522","https://openalex.org/W4407755745","https://openalex.org/W4407808894","https://openalex.org/W4407993232","https://openalex.org/W4408021028","https://openalex.org/W4408078397","https://openalex.org/W4408103111","https://openalex.org/W4408108008","https://openalex.org/W4408145592","https://openalex.org/W4408215141","https://openalex.org/W4409164988","https://openalex.org/W4409177102","https://openalex.org/W4409290141"],"related_works":[],"abstract_inverted_index":{"Direction":[0],"of":[1,78,170],"Arrival":[2],"(DOA)":[3],"estimation":[4,203],"constitutes":[5],"a":[6,56,87,113,153,194],"fundamental":[7],"challenge":[8],"in":[9,31,156,173,188],"array":[10,81],"signal":[11],"processing,":[12],"particularly":[13,187],"under":[14],"low":[15],"SNR":[16,143,165],"conditions":[17],"and":[18,128,139,145,166,185],"limited":[19,205],"snapshot":[20,146],"availability.":[21],"While":[22],"traditional":[23],"subspace":[24],"decomposition":[25],"methods":[26,135],"suffer":[27],"from":[28],"performance":[29],"degradation":[30],"noisy":[32],"environments,":[33],"data-driven":[34],"approaches":[35],"based":[36],"on":[37],"Convolutional":[38],"Neural":[39],"Networks":[40,63],"(CNNs)":[41],"face":[42],"inherent":[43],"limitations":[44],"due":[45],"to":[46,68,94,111,133],"training":[47],"data":[48,66,102,110,179],"scarcity.":[49],"To":[50],"address":[51],"this":[52],"limitation,":[53],"we":[54],"propose":[55],"novel":[57],"framework":[58,151,192],"that":[59,73,99],"integrates":[60],"Generative":[61],"Adversarial":[62],"(GANs)":[64],"for":[65,116,197],"augmentation":[67],"synthesize":[69],"high-fidelity":[70],"covariance":[71,82,97],"matrices":[72,98,105],"preserve":[74],"the":[75,159],"statistical":[76],"characteristics":[77],"physics-based":[79],"simulated":[80],"matrices.":[83],"Our":[84],"method":[85],"employs":[86],"Wasserstein":[88],"GAN":[89],"with":[90,108,204],"Gradient":[91],"Penalty":[92],"(WGAN-GP)":[93],"generate":[95],"synthetic":[96],"mimic":[100],"real":[101,109],"distributions.":[103],"These":[104],"are":[106],"combined":[107],"train":[112],"CNN":[114],"optimized":[115],"DOA":[117,202],"estimation.":[118],"The":[119,148,191],"proposed":[120,149],"GAN-CNN":[121,150],"achieves":[122,152,167],"lower":[123],"Root":[124],"Mean":[125],"Square":[126],"Error":[127],"higher":[129],"prediction":[130],"accuracy":[131],"compared":[132],"baseline":[134,161],"(MUSIC,":[136],"FSS,":[137],"CS":[138],"CNN)":[140],"across":[141],"varying":[142],"levels":[144],"counts.":[147],"33%":[154],"reduction":[155],"RMSE":[157,169],"against":[158],"best":[160],"at":[162],"-20":[163],"dB":[164],"an":[168],"3.45":[171],"\u2218":[172],"50":[174],"snapshots.":[175],"This":[176],"approach":[177],"mitigates":[178],"scarcity":[180],"issues,":[181],"improving":[182],"model":[183],"generalization":[184],"robustness,":[186],"challenging":[189],"environments.":[190],"offers":[193],"practical":[195],"solution":[196],"real-world":[198],"applications":[199],"requiring":[200],"accurate":[201],"resources.":[206]},"counts_by_year":[],"updated_date":"2026-06-18T08:10:14.011955","created_date":"2026-04-15T00:00:00"}
