{"id":"https://openalex.org/W2774183189","doi":"https://doi.org/10.1109/waspaa.2017.8170022","title":"Robust phase replication method for spatial aliasing problem in multiple sound sources localization","display_name":"Robust phase replication method for spatial aliasing problem in multiple sound sources localization","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2774183189","doi":"https://doi.org/10.1109/waspaa.2017.8170022","mag":"2774183189"},"language":"en","primary_location":{"id":"doi:10.1109/waspaa.2017.8170022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa.2017.8170022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","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/A5056322023","display_name":"Kainan Chen","orcid":"https://orcid.org/0000-0002-7231-2404"},"institutions":[{"id":"https://openalex.org/I4210166625","display_name":"Huawei German Research Center","ror":"https://ror.org/00z59w514","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210129353","https://openalex.org/I4210166625"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Kainan Chen","raw_affiliation_strings":["Huawei German Research Center, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Huawei German Research Center, Munich, Germany","institution_ids":["https://openalex.org/I4210166625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030512300","display_name":"J\u00fcrgen T. Geiger","orcid":null},"institutions":[{"id":"https://openalex.org/I4210166625","display_name":"Huawei German Research Center","ror":"https://ror.org/00z59w514","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210129353","https://openalex.org/I4210166625"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jurgen Geiger","raw_affiliation_strings":["Huawei German Research Center, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Huawei German Research Center, Munich, Germany","institution_ids":["https://openalex.org/I4210166625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000570675","display_name":"Wenyu Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210166625","display_name":"Huawei German Research Center","ror":"https://ror.org/00z59w514","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210129353","https://openalex.org/I4210166625"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wenyu Jin","raw_affiliation_strings":["Huawei German Research Center, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Huawei German Research Center, Munich, Germany","institution_ids":["https://openalex.org/I4210166625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101412090","display_name":"Mohammad J. Taghizadeh","orcid":"https://orcid.org/0000-0002-3383-2255"},"institutions":[{"id":"https://openalex.org/I4210166625","display_name":"Huawei German Research Center","ror":"https://ror.org/00z59w514","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210129353","https://openalex.org/I4210166625"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mohammad Taghizadeh","raw_affiliation_strings":["Huawei German Research Center, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Huawei German Research Center, Munich, Germany","institution_ids":["https://openalex.org/I4210166625"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068787682","display_name":"Walter Kellermann","orcid":"https://orcid.org/0000-0002-6501-3174"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Walter Kellermann","raw_affiliation_strings":["Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander-Universitat Erlangen-N\u00fcrnberg, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Multimedia Communications and Signal Processing, Friedrich-Alexander-Universitat Erlangen-N\u00fcrnberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056322023"],"corresponding_institution_ids":["https://openalex.org/I4210166625"],"apc_list":null,"apc_paid":null,"fwci":0.1849,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.48671773,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"406","issue":null,"first_page":"195","last_page":"199"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9988999962806702,"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/computer-science","display_name":"Computer science","score":0.7605639696121216},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6772336959838867},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5796855688095093},{"id":"https://openalex.org/keywords/aliasing","display_name":"Aliasing","score":0.5637068152427673},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5233120918273926},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.41134387254714966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2762317657470703}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7605639696121216},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6772336959838867},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5796855688095093},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.5637068152427673},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5233120918273926},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.41134387254714966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2762317657470703},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/waspaa.2017.8170022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa.2017.8170022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W228326602","https://openalex.org/W771165285","https://openalex.org/W1581848821","https://openalex.org/W1594171365","https://openalex.org/W1974343358","https://openalex.org/W2015143272","https://openalex.org/W2021196544","https://openalex.org/W2031744243","https://openalex.org/W2046317813","https://openalex.org/W2090020898","https://openalex.org/W2090354597","https://openalex.org/W2091764829","https://openalex.org/W2113638573","https://openalex.org/W2121756139","https://openalex.org/W2128131274","https://openalex.org/W2128917116","https://openalex.org/W2130121545","https://openalex.org/W2130356050","https://openalex.org/W2131552695","https://openalex.org/W2160557558","https://openalex.org/W2168140505","https://openalex.org/W2667604394"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2317200988","https://openalex.org/W2100212762","https://openalex.org/W2394004323","https://openalex.org/W2398764543","https://openalex.org/W2027335291","https://openalex.org/W2052122378","https://openalex.org/W2544423928","https://openalex.org/W2053286651"],"abstract_inverted_index":{"Most":[0],"of":[1,97,139],"multichannel":[2],"sound":[3],"source":[4],"Direction":[5],"Of":[6],"Arrival":[7],"(DOA)":[8],"estimation":[9,32],"algorithms":[10],"suffer":[11],"from":[12],"spatial":[13,25],"aliasing":[14,26],"problems.":[15],"The":[16,55,109],"Interchannel":[17],"Phase":[18],"Differences":[19],"(IPDs)":[20],"are":[21,71],"wrapped":[22],"beyond":[23],"the":[24,30,44,65,68,75,81,89,94,98,101,137],"frequency.":[27],"This":[28],"invalidates":[29],"DOA":[31],"due":[33],"to":[34,42,73],"significant":[35],"errors.":[36],"A":[37,125],"real-time":[38],"algorithm":[39,56],"is":[40,104],"proposed":[41],"address":[43],"general":[45],"IPD":[46,60],"wrapping":[47],"problem":[48],"for":[49,121],"both":[50],"single-source":[51],"and":[52,62,128,133],"multi-source":[53],"scenarios.":[54],"comprises":[57],"two":[58],"steps,":[59],"replication":[61,90],"denoising.":[63],"In":[64],"first":[66],"step,":[67],"obtained":[69],"IPDs":[70],"replicated":[72,102],"all":[74],"possible":[76],"2n-periodic":[77],"repetitions,":[78],"thus":[79],"performing":[80],"correct":[82,95],"unwrapping":[83],"while":[84],"introducing":[85],"errors":[86],"inevitably.":[87],"However,":[88],"can":[91],"also":[92],"emphasize":[93],"DOAs":[96],"sources":[99],"when":[100],"matrix":[103],"transformed":[105],"into":[106],"a":[107,113,122],"histogram.":[108],"second":[110],"step":[111],"contains":[112],"post-processing":[114],"method":[115,118],"supporting":[116],"our":[117,140],"more":[119],"robust":[120],"noisy":[123],"environment.":[124],"theoretical":[126],"analysis":[127],"experimental":[129],"results":[130],"with":[131],"simulations":[132],"real":[134],"recordings":[135],"show":[136],"robustness":[138],"method.":[141]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"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"}