{"id":"https://openalex.org/W2913517222","doi":"https://doi.org/10.1109/icdsp.2018.8631636","title":"A Modified Frequency Weighted MUSIC Algorithm for Multiple Sound Sources Localization","display_name":"A Modified Frequency Weighted MUSIC Algorithm for Multiple Sound Sources Localization","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2913517222","doi":"https://doi.org/10.1109/icdsp.2018.8631636","mag":"2913517222"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2018.8631636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","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/A5100650768","display_name":"Shan Gao","orcid":"https://orcid.org/0000-0003-1189-7776"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shan Gao","raw_affiliation_strings":["Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070975831","display_name":"Yankun Huang","orcid":"https://orcid.org/0009-0006-1118-6922"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yankun Huang","raw_affiliation_strings":["Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101672141","display_name":"Tao Zhang","orcid":"https://orcid.org/0000-0003-2317-644X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Zhang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084685506","display_name":"Xihong Wu","orcid":"https://orcid.org/0009-0004-5236-7469"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xihong Wu","raw_affiliation_strings":["Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103080532","display_name":"Tianshu Qu","orcid":"https://orcid.org/0000-0001-6256-2031"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianshu Qu","raw_affiliation_strings":["Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory on Machine Perception(Ministry of Education), Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100650768"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.6606,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71186104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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":1.0,"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":0.9991999864578247,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/multiple-signal-classification","display_name":"Multiple signal classification","score":0.7791679501533508},{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.7488579154014587},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6346213817596436},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.6303847432136536},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5301210284233093},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5034722685813904},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.44051581621170044},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.43004029989242554},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3809013068675995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3780513405799866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22038093209266663},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11068844795227051}],"concepts":[{"id":"https://openalex.org/C206118826","wikidata":"https://www.wikidata.org/wiki/Q3841682","display_name":"Multiple signal classification","level":3,"score":0.7791679501533508},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.7488579154014587},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6346213817596436},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.6303847432136536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5301210284233093},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5034722685813904},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.44051581621170044},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.43004029989242554},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3809013068675995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3780513405799866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22038093209266663},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11068844795227051},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdsp.2018.8631636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2018.8631636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W126779258","https://openalex.org/W1483960856","https://openalex.org/W1969299255","https://openalex.org/W1987906574","https://openalex.org/W2031805580","https://openalex.org/W2046317813","https://openalex.org/W2069432516","https://openalex.org/W2089619278","https://openalex.org/W2113638573","https://openalex.org/W2123577089","https://openalex.org/W2128977628","https://openalex.org/W2151227854","https://openalex.org/W2162848654","https://openalex.org/W2218753925","https://openalex.org/W6605165268"],"related_works":["https://openalex.org/W1858458802","https://openalex.org/W1608626226","https://openalex.org/W2119880556","https://openalex.org/W1969182061","https://openalex.org/W2067714367","https://openalex.org/W2920316261","https://openalex.org/W3167377032","https://openalex.org/W2354828100","https://openalex.org/W2802812753","https://openalex.org/W2913517222"],"abstract_inverted_index":{"The":[0,90,111],"traditional":[1,107],"weighted":[2,38,108],"MUSIC":[3,39,109],"algorithm":[4,40],"is":[5,23,41],"usually":[6],"implemented":[7],"based":[8],"on":[9],"a":[10,36,119],"sparsity":[11],"assumption":[12],"named":[13],"W-Disjoint":[14],"Orthogonality":[15],"(WDO)":[16],"when":[17],"the":[18,45,55,59,67,72,82,86,97,106,115],"number":[19],"of":[20,53,61,75,99],"sound":[21,50],"sources":[22,88],"unknown,":[24],"which":[25,79],"may":[26],"not":[27],"be":[28],"suitable":[29],"in":[30,48,123],"many":[31],"scenarios.":[32],"In":[33],"this":[34],"paper,":[35],"modified":[37],"proposed":[42,101,116],"to":[43,95],"improve":[44],"localization":[46,121],"performance":[47,98],"multiple":[49,87],"sources.":[51],"Instead":[52],"using":[54],"maximum":[56],"eigenvalue":[57],"as":[58,71],"weight":[60,73],"each":[62,76],"frequency":[63,77],"band,":[64,78],"we":[65],"use":[66],"signal-to-noise":[68],"ratio":[69],"(SNR)":[70],"coefficient":[74],"can":[80],"reduce":[81],"disturbance":[83],"cases":[84],"by":[85],"bands.":[89],"simulation":[91],"experiments":[92],"are":[93],"conducted":[94],"evaluate":[96],"our":[100],"method":[102],"and":[103],"compare":[104],"with":[105],"algorithm.":[110],"results":[112],"show":[113],"that":[114],"algorithms":[117],"have":[118],"better":[120],"accuracy":[122],"multiple-source":[124],"environment.":[125]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}