{"id":"https://openalex.org/W3046964793","doi":"https://doi.org/10.1109/spawc48557.2020.9154221","title":"Direction-of-Arrival Estimation in the Low-SNR Regime via a Denoising Autoencoder","display_name":"Direction-of-Arrival Estimation in the Low-SNR Regime via a Denoising Autoencoder","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3046964793","doi":"https://doi.org/10.1109/spawc48557.2020.9154221","mag":"3046964793"},"language":"en","primary_location":{"id":"doi:10.1109/spawc48557.2020.9154221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spawc48557.2020.9154221","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","raw_type":"proceedings-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/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 K. Papageorgiou","raw_affiliation_strings":["School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","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, UK"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK","institution_ids":["https://openalex.org/I32062511"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034605109"],"corresponding_institution_ids":["https://openalex.org/I32062511"],"apc_list":null,"apc_paid":null,"fwci":1.3638,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.81329822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9997000098228455,"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/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/T10860","display_name":"Speech and Audio Processing","score":0.9987000226974487,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/autoencoder","display_name":"Autoencoder","score":0.745198667049408},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6572085022926331},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5286415219306946},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5022473335266113},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.42671605944633484},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4115429222583771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3553037941455841},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3498040437698364},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19569209218025208},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18161249160766602},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12327870726585388}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.745198667049408},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6572085022926331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5286415219306946},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5022473335266113},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.42671605944633484},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4115429222583771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3553037941455841},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3498040437698364},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19569209218025208},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18161249160766602},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12327870726585388},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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":1,"locations":[{"id":"doi:10.1109/spawc48557.2020.9154221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spawc48557.2020.9154221","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1521023302","https://openalex.org/W1522301498","https://openalex.org/W1572063013","https://openalex.org/W1770500012","https://openalex.org/W1974513581","https://openalex.org/W2007675899","https://openalex.org/W2025768430","https://openalex.org/W2115761837","https://openalex.org/W2128131274","https://openalex.org/W2143330906","https://openalex.org/W2149551443","https://openalex.org/W2163922914","https://openalex.org/W2164696938","https://openalex.org/W2296616510","https://openalex.org/W2396734053","https://openalex.org/W2528695050","https://openalex.org/W2897361856","https://openalex.org/W2903096411","https://openalex.org/W2964121744","https://openalex.org/W3016139178","https://openalex.org/W4250955649","https://openalex.org/W6631190155","https://openalex.org/W6730267373"],"related_works":["https://openalex.org/W2883657838","https://openalex.org/W4287995534","https://openalex.org/W3017161237","https://openalex.org/W2998168123","https://openalex.org/W2897995864","https://openalex.org/W2292254049","https://openalex.org/W2883935556","https://openalex.org/W2592385986","https://openalex.org/W2785535669","https://openalex.org/W2610906757"],"abstract_inverted_index":{"The":[0],"performance":[1,96],"of":[2,24,38,100,121,132],"covariance-based":[3,112],"DoA":[4,90,113,123],"estimation":[5,34],"methods":[6,134],"is":[7,85],"limited":[8],"in":[9,12,35,98,105,156],"practice,":[10],"particularly":[11],"the":[13,21,31,36,42,57,65,89,101,106,116,122,130,140,160],"low":[14],"signal-to-noise":[15],"ratio":[16],"(SNR)":[17],"regime,":[18],"due":[19],"to":[20,151],"finite":[22],"number":[23],"observations.":[25],"In":[26],"this":[27],"work,":[28],"we":[29,52,73],"approach":[30,142],"direction-of-arrival":[32],"(DoA)":[33],"presence":[37],"extreme":[39,166],"noise":[40],"from":[41,147],"Machine":[43],"Learning":[44,49],"(ML)":[45],"perspective":[46],"using":[47,110],"Deep":[48],"(DL).":[50],"First,":[51],"derive":[53],"a":[54,68,75,81],"relation":[55],"between":[56],"covariance":[58],"matrix":[59],"and":[60,153],"its":[61],"sample":[62],"estimate":[63],"formulating":[64],"problem":[66],"as":[67,135],"manifold":[69],"learning":[70],"task.":[71],"Next,":[72],"train":[74],"denoising":[76],"autoencoder":[77],"(DAE)":[78],"that":[79,139],"predicts":[80],"Hermitian":[82],"matrix,":[83],"which":[84],"subsequently":[86],"used":[87,155],"for":[88,129],"estimation.":[91],"Experimental":[92],"results":[93],"demonstrate":[94],"significant":[95],"gains":[97],"terms":[99],"root-mean-squared":[102],"error":[103],"(RMSE)":[104],"low-SNR":[107],"regime":[108],"by":[109,165],"popular":[111],"estimators.":[114],"Nevertheless,":[115],"proposed":[117,141],"method":[118],"runs":[119],"independent":[120],"estimator,":[124],"opening":[125],"up":[126],"new":[127],"possibilities":[128],"testing":[131],"other":[133],"well.":[136],"We":[137],"believe":[138],"has":[143],"several":[144],"applications,":[145],"ranging":[146],"wireless":[148],"array":[149],"sensors":[150],"microphones":[152],"transducers":[154],"ultrasound":[157],"imaging,":[158],"where":[159],"operating":[161],"environments":[162],"are":[163],"characterized":[164],"noise.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
