{"id":"https://openalex.org/W2103816858","doi":"https://doi.org/10.1109/taes.2013.6621839","title":"State Estimation in Unknown Non-Gaussian Measurement Noise using Variational Bayesian Technique","display_name":"State Estimation in Unknown Non-Gaussian Measurement Noise using Variational Bayesian Technique","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W2103816858","doi":"https://doi.org/10.1109/taes.2013.6621839","mag":"2103816858"},"language":"en","primary_location":{"id":"doi:10.1109/taes.2013.6621839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2013.6621839","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Aerospace and Electronic Systems","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/A5028028879","display_name":"Hao Zhu","orcid":"https://orcid.org/0000-0003-2222-9722"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhu","raw_affiliation_strings":["Automotive Electronics and Embedded System Engineering Research Center, Department of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China","Dept. of Autom., Chongqing Univ. of Posts & Telecommun., Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Automotive Electronics and Embedded System Engineering Research Center, Department of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]},{"raw_affiliation_string":"Dept. of Autom., Chongqing Univ. of Posts & Telecommun., Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061884304","display_name":"Henry Leung","orcid":"https://orcid.org/0000-0002-5984-107X"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Henry Leung","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada","Dept. of Electr. & Comput. Eng., Univ. of Calgary, Calgary, AB, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100676074","display_name":"Zhongshi He","orcid":"https://orcid.org/0009-0007-3682-0464"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongshi He","raw_affiliation_strings":["Department of Computer Science, Chongqing University, Chongqing, China","[Department of Computer Science, Chongqing University, Chongqing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"[Department of Computer Science, Chongqing University, Chongqing, China]","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9471,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.88776826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"49","issue":"4","first_page":"2601","last_page":"2614"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/gaussian","display_name":"Gaussian","score":0.6375816464424133},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6126686334609985},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5621495246887207},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5004251003265381},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4957171678543091},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4868983328342438},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47384005784988403},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4643234610557556},{"id":"https://openalex.org/keywords/marginal-likelihood","display_name":"Marginal likelihood","score":0.44835054874420166},{"id":"https://openalex.org/keywords/gaussian-random-field","display_name":"Gaussian random field","score":0.4407275915145874},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.43444231152534485},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.42707839608192444},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.42696383595466614},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4266001284122467},{"id":"https://openalex.org/keywords/state-space-representation","display_name":"State-space representation","score":0.42174461483955383},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41302669048309326},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37173157930374146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34478291869163513},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22429034113883972},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.09355127811431885},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07957074046134949}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6375816464424133},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6126686334609985},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5621495246887207},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5004251003265381},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4957171678543091},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4868983328342438},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47384005784988403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4643234610557556},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.44835054874420166},{"id":"https://openalex.org/C51267290","wikidata":"https://www.wikidata.org/wiki/Q5527848","display_name":"Gaussian random field","level":4,"score":0.4407275915145874},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.43444231152534485},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.42707839608192444},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.42696383595466614},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4266001284122467},{"id":"https://openalex.org/C52918065","wikidata":"https://www.wikidata.org/wiki/Q230945","display_name":"State-space representation","level":2,"score":0.42174461483955383},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41302669048309326},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37173157930374146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34478291869163513},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22429034113883972},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.09355127811431885},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07957074046134949},{"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/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/taes.2013.6621839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2013.6621839","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W61015563","https://openalex.org/W95577512","https://openalex.org/W1516111018","https://openalex.org/W1531532259","https://openalex.org/W1663973292","https://openalex.org/W1963718895","https://openalex.org/W1970319972","https://openalex.org/W1971269812","https://openalex.org/W1979731521","https://openalex.org/W1980246751","https://openalex.org/W1996706444","https://openalex.org/W2009086942","https://openalex.org/W2022023686","https://openalex.org/W2043623344","https://openalex.org/W2061893297","https://openalex.org/W2074232022","https://openalex.org/W2087394828","https://openalex.org/W2095376999","https://openalex.org/W2099867508","https://openalex.org/W2102716594","https://openalex.org/W2115979064","https://openalex.org/W2118754959","https://openalex.org/W2120000263","https://openalex.org/W2120211304","https://openalex.org/W2128104012","https://openalex.org/W2128519721","https://openalex.org/W2129078811","https://openalex.org/W2133052936","https://openalex.org/W2134963415","https://openalex.org/W2146065452","https://openalex.org/W2152586694","https://openalex.org/W2153184506","https://openalex.org/W2160337655","https://openalex.org/W2167270514","https://openalex.org/W2170099064","https://openalex.org/W2171618211","https://openalex.org/W2172160462","https://openalex.org/W2502276222","https://openalex.org/W6602473807","https://openalex.org/W6629510986","https://openalex.org/W6679423974","https://openalex.org/W6685329217"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W84255947","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2061347451","https://openalex.org/W2078385989"],"abstract_inverted_index":{"The":[0,70],"problem":[1],"of":[2,6,95],"state":[3],"space":[4],"estimation":[5,110],"linear":[7],"systems":[8],"in":[9,77],"an":[10,108],"unknown":[11,32,52],"non-Gaussian":[12,28],"noise":[13,30],"field":[14],"is":[15,23,41,63],"considered.":[16],"A":[17,34],"finite":[18],"Gaussian":[19,71],"mixture":[20,72],"model":[21,26],"(GMM)":[22],"used":[24],"to":[25,43,65,91],"the":[27,45,51,55,67,78,87,93,96,104],"measurement":[29],"with":[31,113],"statistics.":[33],"variational":[35,56,79],"Bayesian":[36,57,80],"expectation":[37,58],"maximization":[38,81],"(VBEM)":[39],"algorithm":[40],"proposed":[42,97,105],"estimate":[44,66],"system":[46,68],"states":[47],"as":[48,50],"well":[49],"parameters.":[53],"In":[54],"(VBE)":[59],"step,":[60],"approximate":[61],"inference":[62],"established":[64],"state.":[69],"parameters":[73],"are":[74],"then":[75],"updated":[76],"(VBM)":[82],"step.":[83],"We":[84],"also":[85],"derive":[86],"true":[88],"marginal":[89],"posteriors":[90],"verify":[92],"performance":[94,111],"VBEM":[98],"method.":[99],"Computer":[100],"simulations":[101],"show":[102],"that":[103],"method":[106],"has":[107],"improved":[109],"compared":[112],"other":[114],"conventional":[115],"approaches.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}