{"id":"https://openalex.org/W4388757688","doi":"https://doi.org/10.1109/uemcon59035.2023.10316061","title":"Convolutional Neural Network-Based Regression for Direction of Arrival Estimation","display_name":"Convolutional Neural Network-Based Regression for Direction of Arrival Estimation","publication_year":2023,"publication_date":"2023-10-12","ids":{"openalex":"https://openalex.org/W4388757688","doi":"https://doi.org/10.1109/uemcon59035.2023.10316061"},"language":"en","primary_location":{"id":"doi:10.1109/uemcon59035.2023.10316061","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/uemcon59035.2023.10316061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 14th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://digitalcommons.uri.edu/ele_facpubs/1698","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066220733","display_name":"Christopher J. Bell","orcid":"https://orcid.org/0009-0005-6487-5038"},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher J. Bell","raw_affiliation_strings":["University of Rhode Island,Kingston,RI,USA,02881"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rhode Island,Kingston,RI,USA,02881","institution_ids":["https://openalex.org/I17626003"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057521393","display_name":"Kaushallya Adhikari","orcid":"https://orcid.org/0000-0002-0706-0781"},"institutions":[{"id":"https://openalex.org/I17626003","display_name":"University of Rhode Island","ror":"https://ror.org/013ckk937","country_code":"US","type":"education","lineage":["https://openalex.org/I17626003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushallya Adhikari","raw_affiliation_strings":["University of Rhode Island,Kingston,RI,USA,02881"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rhode Island,Kingston,RI,USA,02881","institution_ids":["https://openalex.org/I17626003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089339982","display_name":"Lauren A. Freeman","orcid":"https://orcid.org/0000-0003-4474-4290"},"institutions":[{"id":"https://openalex.org/I2799471739","display_name":"Naval Undersea Warfare Center","ror":"https://ror.org/04bnxa153","country_code":"US","type":"other","lineage":["https://openalex.org/I1328969757","https://openalex.org/I1330347796","https://openalex.org/I2799471739","https://openalex.org/I3130687028"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lauren A. Freeman","raw_affiliation_strings":["Naval Undersea Warfare Center Newport,Newport,RI,USA,02841"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Naval Undersea Warfare Center Newport,Newport,RI,USA,02841","institution_ids":["https://openalex.org/I2799471739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.739,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71090752,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"I","issue":null,"first_page":"0373","last_page":"0379"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7091847658157349},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6223526000976562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5774607062339783},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5760166049003601},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.5226552486419678},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5060643553733826},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49471303820610046},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4876488447189331},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45161014795303345},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.42395520210266113},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.41383638978004456},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31859177350997925},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1732787787914276}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7091847658157349},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6223526000976562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5774607062339783},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5760166049003601},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.5226552486419678},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5060643553733826},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49471303820610046},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4876488447189331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45161014795303345},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.42395520210266113},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.41383638978004456},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31859177350997925},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1732787787914276},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/uemcon59035.2023.10316061","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/uemcon59035.2023.10316061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 14th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"},{"id":"pmh:oai:digitalcommons.uri.edu:ele_facpubs-2698","is_oa":true,"landing_page_url":"https://digitalcommons.uri.edu/ele_facpubs/1698","pdf_url":null,"source":{"id":"https://openalex.org/S2764761010","display_name":"Journal of Media Literacy Education","issn_l":"2167-8715","issn":["2167-8715"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316378","host_organization_name":"National Association for Media Literacy Education","host_organization_lineage":["https://openalex.org/P4310316378"],"host_organization_lineage_names":["National Association for Media Literacy Education"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical, Computer, and Biomedical Engineering Faculty Publications","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:digitalcommons.uri.edu:ele_facpubs-2698","is_oa":true,"landing_page_url":"https://digitalcommons.uri.edu/ele_facpubs/1698","pdf_url":null,"source":{"id":"https://openalex.org/S2764761010","display_name":"Journal of Media Literacy Education","issn_l":"2167-8715","issn":["2167-8715"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310316378","host_organization_name":"National Association for Media Literacy Education","host_organization_lineage":["https://openalex.org/P4310316378"],"host_organization_lineage_names":["National Association for Media Literacy Education"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Electrical, Computer, and Biomedical Engineering Faculty Publications","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W250076511","https://openalex.org/W653761051","https://openalex.org/W1480376833","https://openalex.org/W1506558619","https://openalex.org/W1569512666","https://openalex.org/W1616502035","https://openalex.org/W1869095858","https://openalex.org/W2014042806","https://openalex.org/W2103263585","https://openalex.org/W2113638573","https://openalex.org/W2119554116","https://openalex.org/W2152840263","https://openalex.org/W2584180403","https://openalex.org/W2624972355","https://openalex.org/W2885219692","https://openalex.org/W2897361856","https://openalex.org/W2949768570","https://openalex.org/W2978977033","https://openalex.org/W2989691494","https://openalex.org/W2993165567","https://openalex.org/W3013939384","https://openalex.org/W3015078117","https://openalex.org/W3088998189","https://openalex.org/W3102628653","https://openalex.org/W3103163183","https://openalex.org/W3104690928","https://openalex.org/W4211251910","https://openalex.org/W4214908577","https://openalex.org/W4223454196","https://openalex.org/W4285101252","https://openalex.org/W4294975005"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2167092671","https://openalex.org/W1861706286","https://openalex.org/W2219338811","https://openalex.org/W2149583853","https://openalex.org/W2143002539","https://openalex.org/W4293472652","https://openalex.org/W1120847856","https://openalex.org/W2130386332"],"abstract_inverted_index":{"This":[0],"work":[1],"utilizes":[2],"convolutional":[3],"neural":[4],"networks":[5],"(CNNs)":[6],"to":[7,26,35,42,57,65,85,140],"estimate":[8],"the":[9,28,33,44,52,96,131],"directions":[10],"of":[11,13,20,80,95,145],"arrival":[12],"plane":[14],"waves":[15],"impinging":[16],"on":[17,107],"an":[18],"array":[19],"sensors.":[21],"We":[22,37],"propose":[23],"a":[24],"methodology":[25],"impose":[27],"shift-invariant":[29,97,120],"structure":[30,43,121],"inherent":[31],"in":[32],"data":[34,45,54,62],"CNNs.":[36,58],"use":[38],"several":[39],"input":[40,133],"formulations":[41],"collected":[46],"from":[47],"sensor":[48],"arrays":[49],"and":[50,82,113,126],"feed":[51],"structured":[53],"as":[55],"inputs":[56],"For":[59],"all":[60],"CNNs,":[61],"sets":[63],"corresponding":[64],"different":[66,73,78],"signal-to-noise":[67],"ratios":[68],"(SNR)":[69],"are":[70,75,100,105],"generated.":[71],"Several":[72],"CNNs":[74,99,103],"trained":[76],"using":[77],"pairs":[79],"training":[81],"validation":[83],"SNRs":[84],"investigate":[86],"how":[87],"root":[88],"mean":[89],"square":[90],"error":[91],"(RMSE)":[92],"trends.":[93],"RMSEs":[94],"structure-imposed":[98],"compared":[101],"with":[102],"that":[104,119,144],"based":[106,148],"raw":[108],"data,":[109],"sample":[110],"covariance":[111],"matrices,":[112],"principal":[114],"eigenvectors.":[115],"The":[116],"simulations":[117],"show":[118],"can":[122],"be":[123],"efficiently":[124],"imposed":[125],"has":[127],"lower":[128],"RMSE":[129],"than":[130],"other":[132],"formulations;":[134],"however,":[135],"additional":[136],"refinement":[137],"is":[138],"required":[139],"improve":[141],"performance":[142],"beyond":[143],"classical":[146],"subspace":[147],"DOA":[149],"estimation":[150],"methods.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
