{"id":"https://openalex.org/W7125974975","doi":"https://doi.org/10.1109/lsp.2026.3659037","title":"A Deep Multiscale Wavelet Scattering-Attention Model for Real-Time Underwater DoA Estimation","display_name":"A Deep Multiscale Wavelet Scattering-Attention Model for Real-Time Underwater DoA Estimation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125974975","doi":"https://doi.org/10.1109/lsp.2026.3659037"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2026.3659037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3659037","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5060067187","display_name":"Murtiza Ali","orcid":"https://orcid.org/0000-0001-7593-3380"},"institutions":[{"id":"https://openalex.org/I4210127441","display_name":"Indian Institute of Technology Jammu","ror":"https://ror.org/02f0vsw63","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210127441"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Murtiza Ali","raw_affiliation_strings":["Department of Electrical Engineering at the Indian Institute of Technology Jammu, Jammu, India"],"raw_orcid":"https://orcid.org/0000-0001-7593-3380","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering at the Indian Institute of Technology Jammu, Jammu, India","institution_ids":["https://openalex.org/I4210127441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107339473","display_name":"Karan Nathwani","orcid":"https://orcid.org/0000-0002-0678-2328"},"institutions":[{"id":"https://openalex.org/I4210127441","display_name":"Indian Institute of Technology Jammu","ror":"https://ror.org/02f0vsw63","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210127441"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Karan Nathwani","raw_affiliation_strings":["Department of Electrical Engineering at the Indian Institute of Technology Jammu, Jammu, India"],"raw_orcid":"https://orcid.org/0000-0002-0678-2328","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering at the Indian Institute of Technology Jammu, Jammu, India","institution_ids":["https://openalex.org/I4210127441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210127441"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10450214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"843","last_page":"847"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9118000268936157,"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":0.9118000268936157,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.04540000110864639,"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"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.008500000461935997,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/multipath-propagation","display_name":"Multipath propagation","score":0.6818000078201294},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6694999933242798},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.6365000009536743},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.550599992275238},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4943999946117401},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44359999895095825},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4397999942302704},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4293000102043152}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7186999917030334},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.6818000078201294},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6694999933242798},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.6365000009536743},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.550599992275238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5320000052452087},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4943999946117401},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44359999895095825},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4397999942302704},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4293000102043152},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4074000120162964},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.40450000762939453},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.39559999108314514},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.38609999418258667},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C205312793","wikidata":"https://www.wikidata.org/wiki/Q16002801","display_name":"Ambient noise level","level":3,"score":0.3621000051498413},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3337000012397766},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C169111936","wikidata":"https://www.wikidata.org/wiki/Q424098","display_name":"Underwater acoustic communication","level":3,"score":0.2904999852180481},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.28519999980926514},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C174943157","wikidata":"https://www.wikidata.org/wiki/Q810826","display_name":"Bathymetry","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2026.3659037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3659037","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.7957296371459961}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1994477821","https://openalex.org/W2042565723","https://openalex.org/W2060041163","https://openalex.org/W2066218102","https://openalex.org/W2103519107","https://openalex.org/W2113638573","https://openalex.org/W2136172079","https://openalex.org/W2139451096","https://openalex.org/W2161872841","https://openalex.org/W2406727662","https://openalex.org/W2411175614","https://openalex.org/W2483969342","https://openalex.org/W2591434033","https://openalex.org/W2625541168","https://openalex.org/W2753756265","https://openalex.org/W2897361856","https://openalex.org/W2912403396","https://openalex.org/W3003257820","https://openalex.org/W3017303452","https://openalex.org/W3022667867","https://openalex.org/W3104690928","https://openalex.org/W3135420869","https://openalex.org/W3154017625","https://openalex.org/W4206463209","https://openalex.org/W4255098125","https://openalex.org/W4282946978","https://openalex.org/W4293193223","https://openalex.org/W4311763873","https://openalex.org/W4383271646","https://openalex.org/W4391615871","https://openalex.org/W4403643603","https://openalex.org/W4405303704","https://openalex.org/W4407574627"],"related_works":[],"abstract_inverted_index":{"Direction-of-arrival":[0],"(DoA)":[1],"estimation":[2,36],"is":[3,10,44,135],"vital":[4],"for":[5,34,132,184],"underwater":[6,40,52],"target":[7],"localisation":[8],"but":[9],"challenged":[11],"by":[12],"multipath":[13,102,179],"propagation":[14,103],"and":[15,69,77,91,110],"noise":[16,112,177],"in":[17,37,148],"dynamic":[18],"ocean":[19],"environments.":[20],"To":[21,95],"tackle":[22],"such":[23],"issues,":[24],"we":[25,100],"introduce":[26],"the":[27,38,138,163],"multiscale":[28],"attentive":[29],"wavelet":[30,70],"scattering":[31,71],"fusion":[32],"(MAWSF)":[33],"DoA":[35,150],"challenging":[39],"environment.":[41],"This":[42],"MAWSF":[43,61,134],"a":[45,126],"deep":[46],"learning-based":[47],"network,":[48],"trained":[49],"on":[50,137],"simulated":[51],"data,":[53],"capable":[54],"of":[55,156,165,176],"generalising":[56],"to":[57,73,80,87,118],"real":[58,97,139],"oceanic":[59,98],"scenarios.":[60],"performs":[62],"multi-scale":[63],"feature":[64],"extraction":[65],"using":[66],"directional":[67],"convolutions":[68],"transforms":[72],"capture":[74],"spatial":[75,121],"patterns":[76],"enhance":[78,92],"robustness":[79],"noise.":[81],"It":[82,152],"also":[83],"employs":[84],"attention":[85],"mechanisms":[86],"model":[88],"global":[89],"dependencies":[90],"context":[93],"awareness.":[94],"emulate":[96],"conditions,":[99],"simulate":[101],"along":[104],"with":[105,125],"varying":[106],"source-receiver":[107],"depths,":[108],"ranges,":[109],"ambient":[111],"levels.":[113],"These":[114],"simulations":[115],"are":[116],"used":[117],"generate":[119],"multi-channel":[120],"covariance":[122],"matrices":[123],"labelled":[124],"one-hot":[127],"encoded":[128],"true":[129],"DoAs":[130],"vector":[131],"training.":[133],"evaluated":[136],"SWellEx-96":[140],"dataset,":[141],"where":[142],"it":[143,171,182],"demonstrated":[144],"high":[145],"angular":[146],"resolution":[147],"offgrid":[149],"estimation.":[151],"achieves":[153],"an":[154],"RMSE":[155],"<inline-formula":[157],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[158],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[159],"notation=\"LaTeX\">$14.76^{\\circ":[160],"}$</tex-math></inline-formula>,":[161],"surpassing":[162],"performance":[164],"state-of-the-art":[166],"networks.":[167],"Unlike":[168],"traditional":[169],"methods,":[170],"requires":[172],"no":[173],"prior":[174],"knowledge":[175],"or":[178],"counts,":[180],"making":[181],"well-suited":[183],"real-time":[185],"applications.":[186]},"counts_by_year":[],"updated_date":"2026-02-13T13:36:01.753593","created_date":"2026-01-29T00:00:00"}
