{"id":"https://openalex.org/W4388118217","doi":"https://doi.org/10.23919/eusipco58844.2023.10290026","title":"A Toeplitz Prior-Based Deep Learning Framework for DOA Estimation with Unknown Mutual Coupling","display_name":"A Toeplitz Prior-Based Deep Learning Framework for DOA Estimation with Unknown Mutual Coupling","publication_year":2023,"publication_date":"2023-09-04","ids":{"openalex":"https://openalex.org/W4388118217","doi":"https://doi.org/10.23919/eusipco58844.2023.10290026"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco58844.2023.10290026","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco58844.2023.10290026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","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/A5070144919","display_name":"Zhuoqian Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuoqian Jiang","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031227866","display_name":"Jingmin Xin","orcid":"https://orcid.org/0000-0003-1906-2327"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingmin Xin","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056948991","display_name":"Weiliang Zuo","orcid":"https://orcid.org/0000-0002-8125-7072"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiliang Zuo","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China","Shunan Academy of Artificial Intelligence, Ningbo, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Shunan Academy of Artificial Intelligence, Ningbo, Zhejiang, China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047405956","display_name":"Nanning Zheng","orcid":"https://orcid.org/0000-0003-1608-8257"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nanning Zheng","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University,Xi'an,China,710049","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"National Engineering Laboratory for Visual Information Processing and Applications, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070701022","display_name":"Akira Sano","orcid":"https://orcid.org/0000-0002-9044-9113"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Sano","raw_affiliation_strings":["Keio University,Department of System Design Engineering,Yokohama,Japan,223\u20138522"],"affiliations":[{"raw_affiliation_string":"Keio University,Department of System Design Engineering,Yokohama,Japan,223\u20138522","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070144919"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.5957,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66460051,"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":"1544","last_page":"1548"},"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":0.9994999766349792,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9984999895095825,"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/toeplitz-matrix","display_name":"Toeplitz matrix","score":0.9150837659835815},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.7728127241134644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6407306790351868},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6144688129425049},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5824975371360779},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5595272183418274},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.5491172075271606},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.49208492040634155},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.46197545528411865},{"id":"https://openalex.org/keywords/coupling","display_name":"Coupling (piping)","score":0.45910003781318665},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.44098642468452454},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.41444191336631775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4092484712600708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.406546950340271},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27711960673332214},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.160027414560318},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08645060658454895},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07868942618370056},{"id":"https://openalex.org/keywords/antenna","display_name":"Antenna (radio)","score":0.06533399224281311}],"concepts":[{"id":"https://openalex.org/C147710293","wikidata":"https://www.wikidata.org/wiki/Q849428","display_name":"Toeplitz matrix","level":2,"score":0.9150837659835815},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.7728127241134644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407306790351868},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6144688129425049},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5824975371360779},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5595272183418274},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.5491172075271606},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.49208492040634155},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.46197545528411865},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.45910003781318665},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.44098642468452454},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.41444191336631775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4092484712600708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.406546950340271},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27711960673332214},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.160027414560318},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08645060658454895},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07868942618370056},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.06533399224281311},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco58844.2023.10290026","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco58844.2023.10290026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1920403133","display_name":null,"funder_award_id":"2021ZD0113603","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":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1963799790","https://openalex.org/W2007561267","https://openalex.org/W2096710051","https://openalex.org/W2113638573","https://openalex.org/W2124849030","https://openalex.org/W2128131274","https://openalex.org/W2155421090","https://openalex.org/W2162654459","https://openalex.org/W2164676612","https://openalex.org/W2170762581","https://openalex.org/W2753338871","https://openalex.org/W2892433162","https://openalex.org/W2897361856","https://openalex.org/W2919115771","https://openalex.org/W2963603114","https://openalex.org/W3104690928","https://openalex.org/W3154017625","https://openalex.org/W4205896963","https://openalex.org/W4293193223","https://openalex.org/W4312593598","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W2353873167","https://openalex.org/W2921280830","https://openalex.org/W2126916073","https://openalex.org/W2887132723","https://openalex.org/W2572601863","https://openalex.org/W2038723318","https://openalex.org/W1679731869","https://openalex.org/W2170667396","https://openalex.org/W2886934452","https://openalex.org/W2024369332"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,32,89],"explore":[4],"the":[5,54,64,77,95,112,119,125,132,137,149,164],"problem":[6],"of":[7,63,97,104,122],"direction-of-arrival":[8],"(DOA)":[9],"estimation":[10,159],"with":[11],"unknown":[12],"mutual":[13,83],"coupling":[14,84],"using":[15],"a":[16,36,43,91],"deep":[17],"learning":[18],"(DL)":[19],"framework":[20],"which":[21],"is":[22,73,109],"based":[23],"on":[24,101],"Toeplitz":[25,65],"prior.":[26],"First,":[27],"for":[28,115],"source":[29,44],"number":[30,45],"estimation,":[31],"model":[33],"it":[34],"as":[35],"multi-":[37],"label":[38],"classification":[39],"task":[40],"and":[41,85,106],"build":[42],"detection":[46,120],"network":[47,71],"(SNDN)":[48],"to":[49,75,93,110,118],"learn":[50],"relevant":[51],"information":[52],"in":[53,154],"real":[55],"sample":[56],"covariance":[57,69,79,134],"matrix.":[58],"Next,":[59],"taking":[60],"full":[61],"advantage":[62],"structure,":[66],"an":[67],"ideal":[68,78],"reconstruction":[70],"(ICRN)":[72],"proposed":[74,144],"recover":[76],"matrix":[80,135],"free":[81],"from":[82,131],"noise":[86],"interference.":[87],"Furthermore,":[88],"design":[90],"database":[92],"store":[94],"parameters":[96,114],"ICRN":[98,116],"after":[99],"training":[100],"different":[102],"numbers":[103],"sources,":[105],"its":[107,157],"role":[108],"load":[111],"corresponding":[113],"according":[117],"results":[121,141],"SNDN.":[123],"Finally,":[124],"DOAs":[126],"can":[127,161],"be":[128],"easily":[129],"estimated":[130],"restored":[133],"by":[136],"MUSIC.":[138],"The":[139],"simulation":[140],"show":[142],"our":[143],"approach":[145],"not":[146],"only":[147],"outperforms":[148],"existing":[150],"classical":[151],"methods,":[152],"but":[153],"some":[155],"cases":[156],"DOA":[158],"accuracy":[160],"even":[162],"exceed":[163],"Cramer-Rao":[165],"Lower":[166],"Bound.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}