{"id":"https://openalex.org/W3135997576","doi":"https://doi.org/10.1186/s13634-021-00770-2","title":"Low complexity sparse beamspace DOA estimation via single measurement vectors for uniform circular array","display_name":"Low complexity sparse beamspace DOA estimation via single measurement vectors for uniform circular array","publication_year":2021,"publication_date":"2021-07-30","ids":{"openalex":"https://openalex.org/W3135997576","doi":"https://doi.org/10.1186/s13634-021-00770-2","mag":"3135997576"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-021-00770-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-021-00770-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00770-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00770-2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001442753","display_name":"Di Zhao","orcid":"https://orcid.org/0000-0003-4527-338X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Di Zhao","raw_affiliation_strings":["The 54th Research Institute of CETC, Shijiazhuang, 050081, China","Wireless Network Positioning and Communication Integration Research Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China"],"raw_orcid":"https://orcid.org/0000-0003-4527-338X","affiliations":[{"raw_affiliation_string":"The 54th Research Institute of CETC, Shijiazhuang, 050081, China","institution_ids":[]},{"raw_affiliation_string":"Wireless Network Positioning and Communication Integration Research Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067538819","display_name":"Weijie Tan","orcid":"https://orcid.org/0000-0001-6590-5757"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijie Tan","raw_affiliation_strings":["State Key Laboratory of Public Big Data, Guizhou Big Data Academy, Guizhou University, Guiyang, 550025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou Big Data Academy, Guizhou University, Guiyang, 550025, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102222671","display_name":"Zhongliang Deng","orcid":"https://orcid.org/0000-0002-1984-8613"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongliang Deng","raw_affiliation_strings":["Wireless Network Positioning and Communication Integration Research Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wireless Network Positioning and Communication Integration Research Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100438769","display_name":"Gang Li","orcid":"https://orcid.org/0000-0003-1583-641X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gang Li","raw_affiliation_strings":["The 54th Research Institute of CETC, Shijiazhuang, 050081, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The 54th Research Institute of CETC, Shijiazhuang, 050081, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001442753"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":1665,"currency":"USD","value_usd":1665},"apc_paid":{"value":1665,"currency":"USD","value_usd":1665},"fwci":0.4175,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.58266261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11946","display_name":"Antenna Design and Optimization","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10860","display_name":"Speech and Audio Processing","score":0.9965000152587891,"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/vectorization","display_name":"Vectorization (mathematics)","score":0.6479374170303345},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6464080810546875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6346284747123718},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5335128307342529},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4962056279182434},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.46895164251327515},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44862064719200134},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.447581022977829},{"id":"https://openalex.org/keywords/signal-subspace","display_name":"Signal subspace","score":0.4440799653530121},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.42066097259521484},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3265106976032257},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30109626054763794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15527686476707458},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12114390730857849}],"concepts":[{"id":"https://openalex.org/C41681595","wikidata":"https://www.wikidata.org/wiki/Q7917855","display_name":"Vectorization (mathematics)","level":2,"score":0.6479374170303345},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6464080810546875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6346284747123718},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5335128307342529},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4962056279182434},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.46895164251327515},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44862064719200134},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.447581022977829},{"id":"https://openalex.org/C2777121530","wikidata":"https://www.wikidata.org/wiki/Q7512739","display_name":"Signal subspace","level":4,"score":0.4440799653530121},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.42066097259521484},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3265106976032257},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30109626054763794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15527686476707458},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12114390730857849},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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:10.1186/s13634-021-00770-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-021-00770-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00770-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:40ad9caa72624c4cb33f9c995b03927e","is_oa":true,"landing_page_url":"https://doaj.org/article/40ad9caa72624c4cb33f9c995b03927e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2021, Iss 1, Pp 1-20 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-021-00770-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-021-00770-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00770-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4820366431","display_name":null,"funder_award_id":"2016YFB0502001","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3135997576.pdf","grobid_xml":"https://content.openalex.org/works/W3135997576.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2018419043","https://openalex.org/W2028599779","https://openalex.org/W2091373577","https://openalex.org/W2097610668","https://openalex.org/W2103519107","https://openalex.org/W2113638573","https://openalex.org/W2116295287","https://openalex.org/W2120364464","https://openalex.org/W2129638195","https://openalex.org/W2130342534","https://openalex.org/W2131797282","https://openalex.org/W2148982591","https://openalex.org/W2162409952","https://openalex.org/W2168837636","https://openalex.org/W2228268802","https://openalex.org/W2782452293","https://openalex.org/W2785637931","https://openalex.org/W2804792817","https://openalex.org/W2804815803","https://openalex.org/W2897710113","https://openalex.org/W2901719513","https://openalex.org/W2924119777","https://openalex.org/W2937331273","https://openalex.org/W2944432420","https://openalex.org/W2970657507","https://openalex.org/W2988853056","https://openalex.org/W2997199308","https://openalex.org/W3023507614","https://openalex.org/W3098194984","https://openalex.org/W3105708125","https://openalex.org/W3139527032","https://openalex.org/W4248040551"],"related_works":["https://openalex.org/W2355891660","https://openalex.org/W2164635412","https://openalex.org/W89478532","https://openalex.org/W2532156682","https://openalex.org/W2801687921","https://openalex.org/W2354351449","https://openalex.org/W2462138637","https://openalex.org/W4387444271","https://openalex.org/W2360754927","https://openalex.org/W2372955329"],"abstract_inverted_index":{"Abstract":[0],"In":[1,20],"this":[2],"paper,":[3],"we":[4,24],"present":[5],"a":[6,65,106,115],"low":[7,159],"complexity":[8,169],"sparse":[9,68,95],"beamspace":[10,28,50,69],"direction-of-arrival":[11],"(DOA)":[12],"estimation":[13,102,174],"method":[14,147],"for":[15],"uniform":[16,45],"circular":[17],"array":[18,47,62],"(UCA).":[19],"the":[21,27,33,55,59,79,87,100,112,119,128,131,141,145,155],"proposed":[22,132,146],"method,":[23],"firstly":[25],"use":[26],"transformation":[29],"(BT)":[30],"to":[31,41,126],"transform":[32],"signal":[34,63,70],"model":[35,71],"of":[36,43,82,94,114,118,130,140,143],"UCA":[37],"in":[38,49,158],"element-space":[39],"domain":[40],"that":[42,137],"virtual":[44,60],"linear":[46],"(ULA)":[48],"domain.":[51],"Subsequently,":[52],"by":[53,86,110],"applying":[54],"vectoring":[56],"operator":[57],"on":[58,75],"ULA-like":[61],"model,":[64],"novel":[66],"dimension-reduction":[67],"is":[72,84,103],"derived":[73],"based":[74],"Khatri-Rao":[76],"(KR)":[77],"product,":[78],"observation":[80],"data":[81],"which":[83],"represented":[85],"single":[88],"measurement":[89],"vectors":[90],"(SMVs)":[91],"via":[92],"vectorization":[93],"covariance":[96],"matrix.":[97],"And":[98],"then,":[99],"DOA":[101,152,173],"formulated":[104],"as":[105],"convex":[107],"optimization":[108],"problem":[109],"following":[111],"concept":[113],"sparse-signal-representation":[116],"(SSR)":[117],"SMVs.":[120],"Finally,":[121],"simulations":[122],"are":[123],"carried":[124],"out":[125],"validate":[127],"effectiveness":[129],"method.":[133],"The":[134],"results":[135],"show":[136],"without":[138],"knowledge":[139],"number":[142],"signals,":[144],"not":[148],"only":[149],"has":[150,165],"higher":[151],"resolution":[153],"than":[154,170],"subspace-based":[156],"methods":[157],"signal-to-noise":[160],"ratio":[161],"(SNR),":[162],"but":[163],"also":[164],"far":[166],"lower":[167],"computational":[168],"other":[171],"sparse-like":[172],"methods.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
