{"id":"https://openalex.org/W2945889962","doi":"https://doi.org/10.1109/lcomm.2019.2911518","title":"Maximum-Likelihood Direction Finding Under Elliptical Noise Using the EM Algorithm","display_name":"Maximum-Likelihood Direction Finding Under Elliptical Noise Using the EM Algorithm","publication_year":2019,"publication_date":"2019-05-21","ids":{"openalex":"https://openalex.org/W2945889962","doi":"https://doi.org/10.1109/lcomm.2019.2911518","mag":"2945889962"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2019.2911518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2019.2911518","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-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/A5100382711","display_name":"Ebrahim Baktash","orcid":"https://orcid.org/0000-0003-3744-2139"},"institutions":[{"id":"https://openalex.org/I166459259","display_name":"Shiraz University","ror":"https://ror.org/028qtbk54","country_code":"IR","type":"education","lineage":["https://openalex.org/I166459259"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Ebrahim Baktash","raw_affiliation_strings":["School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran"],"raw_orcid":"https://orcid.org/0000-0003-3744-2139","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran","institution_ids":["https://openalex.org/I166459259"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036406617","display_name":"Mahmood Karimi","orcid":"https://orcid.org/0000-0002-7100-6042"},"institutions":[{"id":"https://openalex.org/I166459259","display_name":"Shiraz University","ror":"https://ror.org/028qtbk54","country_code":"IR","type":"education","lineage":["https://openalex.org/I166459259"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mahmood Karimi","raw_affiliation_strings":["School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran","institution_ids":["https://openalex.org/I166459259"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100382658","display_name":"Xiaodong Wang","orcid":"https://orcid.org/0000-0002-2945-9240"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaodong Wang","raw_affiliation_strings":["Electrical Engineering Department, Columbia University, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-2945-9240","affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100382711"],"corresponding_institution_ids":["https://openalex.org/I166459259"],"apc_list":null,"apc_paid":null,"fwci":1.0015,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.75872146,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"23","issue":"6","first_page":"1041","last_page":"1044"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9934999942779541,"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":0.9911999702453613,"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/direction-of-arrival","display_name":"Direction of arrival","score":0.7441138029098511},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6523184180259705},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6467293500900269},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.6436915397644043},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6391582489013672},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6142687797546387},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5547526478767395},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5365476608276367},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5272266864776611},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5245404839515686},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5218345522880554},{"id":"https://openalex.org/keywords/maximum-likelihood-sequence-estimation","display_name":"Maximum likelihood sequence estimation","score":0.486227422952652},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.46097177267074585},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.4513690173625946},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4484010338783264},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44111713767051697},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.43928900361061096},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3394184410572052},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3103601336479187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16847637295722961},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12726116180419922},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11279034614562988},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.09802037477493286}],"concepts":[{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.7441138029098511},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6523184180259705},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6467293500900269},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.6436915397644043},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6391582489013672},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6142687797546387},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5547526478767395},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5365476608276367},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5272266864776611},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5245404839515686},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5218345522880554},{"id":"https://openalex.org/C191462741","wikidata":"https://www.wikidata.org/wiki/Q6795902","display_name":"Maximum likelihood sequence estimation","level":3,"score":0.486227422952652},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.46097177267074585},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.4513690173625946},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4484010338783264},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44111713767051697},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.43928900361061096},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3394184410572052},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3103601336479187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16847637295722961},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12726116180419922},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11279034614562988},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.09802037477493286},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/lcomm.2019.2911518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2019.2911518","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6554180069","display_name":null,"funder_award_id":"00201510","funder_id":"https://openalex.org/F4320327783","funder_display_name":"Leading Talents Program of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320327783","display_name":"Leading Talents Program of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1956130478","https://openalex.org/W1992511687","https://openalex.org/W2049633694","https://openalex.org/W2783401216","https://openalex.org/W2952350176","https://openalex.org/W6640783133"],"related_works":["https://openalex.org/W1978153144","https://openalex.org/W102848802","https://openalex.org/W1512911331","https://openalex.org/W1575258345","https://openalex.org/W2122958477","https://openalex.org/W2119037098","https://openalex.org/W2025556230","https://openalex.org/W2150616621","https://openalex.org/W2150061385","https://openalex.org/W2187551048"],"abstract_inverted_index":{"Unlike":[0],"subspace-based":[1],"solutions":[2,28],"of":[3,56],"direction-of-arrival":[4],"(DOA)":[5],"estimation":[6,23],"under":[7,33,52],"non-Gaussian":[8],"noise,":[9],"where":[10],"the":[11,16,20,34,48,53],"only":[12],"optional":[13],"difference":[14],"with":[15],"Gaussian":[17],"case":[18],"is":[19],"scatter/covariance":[21],"matrix":[22],"method,":[24],"maximum-likelihood":[25],"(ML)-based":[26],"DOA":[27,45],"need":[29],"a":[30,42],"different":[31],"treatment":[32],"non-Gaussianity":[35],"assumption.":[36],"In":[37],"this":[38],"letter,":[39],"we":[40],"derive":[41],"particular":[43],"ML-based":[44],"solution,":[46],"called":[47],"expectation-maximization":[49],"(EM)":[50],"estimator,":[51],"wide":[54],"class":[55],"complex":[57],"elliptically":[58],"symmetric":[59],"(CES)":[60],"distributions.":[61]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}