{"id":"https://openalex.org/W3104690928","doi":"https://doi.org/10.1109/tsp.2021.3089927","title":"Deep Networks for Direction-of-Arrival Estimation in Low SNR","display_name":"Deep Networks for Direction-of-Arrival Estimation in Low SNR","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3104690928","doi":"https://doi.org/10.1109/tsp.2021.3089927","mag":"3104690928"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2021.3089927","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2021.3089927","pdf_url":"https://ieeexplore.ieee.org/ielx7/78/9307529/09457195.pdf","source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/78/9307529/09457195.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034605109","display_name":"\u0393\u03b5\u03ce\u03c1\u03b3\u03b9\u03bf\u03c2 \u03a0\u03b1\u03c0\u03b1\u03b3\u03b5\u03c9\u03c1\u03b3\u03af\u03bf\u03c5","orcid":"https://orcid.org/0000-0003-2188-8531"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Georgios Papageorgiou","raw_affiliation_strings":["School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2188-8531","affiliations":[{"raw_affiliation_string":"School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071345719","display_name":"Mathini Sellathurai","orcid":"https://orcid.org/0000-0002-8738-8583"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mathini Sellathurai","raw_affiliation_strings":["School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8738-8583","affiliations":[{"raw_affiliation_string":"School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005913897","display_name":"Yonina C. Eldar","orcid":"https://orcid.org/0000-0003-4358-5304"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yonina Eldar","raw_affiliation_strings":["Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel"],"raw_orcid":"https://orcid.org/0000-0003-4358-5304","affiliations":[{"raw_affiliation_string":"Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034605109"],"corresponding_institution_ids":["https://openalex.org/I32062511"],"apc_list":null,"apc_paid":null,"fwci":28.7164,"has_fulltext":true,"cited_by_count":342,"citation_normalized_percentile":{"value":0.99886166,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"69","issue":null,"first_page":"3714","last_page":"3729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9994999766349792,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9994999766349792,"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/T10860","display_name":"Speech and Audio Processing","score":0.9991999864578247,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7270714044570923},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6820831894874573},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.6115319728851318},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5718238353729248},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5586881637573242},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5546928644180298},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.46530941128730774},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.43427011370658875},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3839886486530304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3700135350227356},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20640531182289124},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12026333808898926}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7270714044570923},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6820831894874573},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.6115319728851318},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5718238353729248},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5586881637573242},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5546928644180298},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.46530941128730774},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.43427011370658875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3839886486530304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3700135350227356},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20640531182289124},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12026333808898926},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2021.3089927","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2021.3089927","pdf_url":"https://ieeexplore.ieee.org/ielx7/78/9307529/09457195.pdf","source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2011.08848","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.08848","pdf_url":"https://arxiv.org/pdf/2011.08848","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1109/tsp.2021.3089927","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tsp.2021.3089927","pdf_url":"https://ieeexplore.ieee.org/ielx7/78/9307529/09457195.pdf","source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6593306550","display_name":"A Unified Multiple Access Framework for Next Generation Mobile Networks By Removing Orthogonality (MANGO)","funder_award_id":"EP/P009670/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8402760336","display_name":null,"funder_award_id":"EP/P009670/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3104690928.pdf","grobid_xml":"https://content.openalex.org/works/W3104690928.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W340244495","https://openalex.org/W1521023302","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1952629836","https://openalex.org/W1964521756","https://openalex.org/W2015418199","https://openalex.org/W2098174516","https://openalex.org/W2112796928","https://openalex.org/W2116414176","https://openalex.org/W2118693125","https://openalex.org/W2123457453","https://openalex.org/W2123930706","https://openalex.org/W2128131274","https://openalex.org/W2137983211","https://openalex.org/W2147276092","https://openalex.org/W2156005716","https://openalex.org/W2164696938","https://openalex.org/W2164787613","https://openalex.org/W2251966340","https://openalex.org/W2296319761","https://openalex.org/W2296616510","https://openalex.org/W2357400875","https://openalex.org/W2528695050","https://openalex.org/W2557283755","https://openalex.org/W2584180403","https://openalex.org/W2611943505","https://openalex.org/W2768511943","https://openalex.org/W2810871807","https://openalex.org/W2885219692","https://openalex.org/W2897361856","https://openalex.org/W2903096411","https://openalex.org/W2919115771","https://openalex.org/W2952350176","https://openalex.org/W2962683884","https://openalex.org/W2962949934","https://openalex.org/W2963326253","https://openalex.org/W2964121744","https://openalex.org/W2978977033","https://openalex.org/W2981577131","https://openalex.org/W2989691494","https://openalex.org/W3014801121","https://openalex.org/W3103163183","https://openalex.org/W3104757150","https://openalex.org/W3105475478","https://openalex.org/W3146803896","https://openalex.org/W4244779849","https://openalex.org/W4250955649","https://openalex.org/W4252189235","https://openalex.org/W4300263211","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6769545059"],"related_works":["https://openalex.org/W4388311650","https://openalex.org/W5922282","https://openalex.org/W1974056099","https://openalex.org/W4245343541","https://openalex.org/W2386077341","https://openalex.org/W563589758","https://openalex.org/W62490179","https://openalex.org/W4382204317","https://openalex.org/W2100915163","https://openalex.org/W2113817303"],"abstract_inverted_index":{"In":[0,18],"this":[1],"work,":[2],"we":[3,20,61,142],"consider":[4],"direction-of-arrival":[5],"(DoA)":[6],"estimation":[7],"in":[8,50,86,117,133,185,190],"the":[9,32,45,51,63,72,87,108,118,127,144,147,161,170,179],"presence":[10,88],"of":[11,44,89,98,129,136,149,178],"extreme":[12],"noise":[13],"using":[14,31],"Deep":[15],"Learning":[16],"(DL).":[17],"particular,":[19],"introduce":[21],"a":[22,66,94,153,157],"Convolutional":[23],"Neural":[24],"Network":[25],"(CNN)":[26],"that":[27,146,188],"predicts":[28],"angular":[29],"directions":[30],"sample":[33],"covariance":[34],"matrix":[35,49],"estimate.":[36],"The":[37,80,175],"network":[38],"is":[39,102,151,182],"trained":[40],"from":[41,194],"multi-channel":[42],"data":[43],"true":[46],"array":[47,196],"manifold":[48],"low":[52],"signal-to-noise-ratio":[53],"(SNR)":[54],"regime.":[55],"By":[56],"adopting":[57],"an":[58],"on-grid":[59],"approach,":[60],"model":[62],"problem":[64],"as":[65],"multi-label":[67],"classification":[68],"task":[69],"and":[70,91,125,138,155,168],"train":[71],"CNN":[73,162],"to":[74,93,104,122,164,198],"predict":[75,169],"DoAs":[76,171],"across":[77],"all":[78],"SNRs.":[79],"proposed":[81,180],"architecture":[82],"demonstrates":[83],"enhanced":[84],"robustness":[85,177],"noise,":[90],"resilience":[92],"relatively":[95],"small":[96],"number":[97,148,167],"snapshots.":[99],"Moreover,":[100],"it":[101],"able":[103],"resolve":[105],"angles":[106],"within":[107],"grid":[109],"resolution.":[110],"Experimental":[111],"results":[112],"demonstrate":[113],"significant":[114],"performance":[115],"gains":[116],"low-SNR":[119],"regime":[120],"compared":[121],"state-of-the-art":[123],"methods":[124],"without":[126],"requirement":[128],"any":[130],"parameter":[131],"tuning":[132],"both":[134],"cases":[135],"correlated":[137],"uncorrelated":[139],"sources.":[140],"Finally,":[141],"relax":[143],"assumption":[145],"sources":[150],"known":[152],"priori":[154],"present":[156],"training":[158],"method,":[159],"where":[160],"learns":[163],"infer":[165],"their":[166],"with":[172],"high":[173],"confidence.":[174],"increased":[176],"solution":[181],"highly":[183],"desirable":[184],"challenging":[186],"scenarios":[187],"arise":[189],"several":[191],"fields,":[192],"ranging":[193],"wireless":[195],"sensors":[197],"acoustic":[199],"microphones":[200],"or":[201],"sonars.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":35},{"year":2025,"cited_by_count":121},{"year":2024,"cited_by_count":88},{"year":2023,"cited_by_count":61},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":10}],"updated_date":"2026-06-04T09:04:59.091469","created_date":"2025-10-10T00:00:00"}