{"id":"https://openalex.org/W2517464434","doi":"https://doi.org/10.1109/tsp.2018.2865434","title":"Skew-$t$ Filter and Smoother With Improved Covariance Matrix Approximation","display_name":"Skew-$t$ Filter and Smoother With Improved Covariance Matrix Approximation","publication_year":2018,"publication_date":"2018-08-14","ids":{"openalex":"https://openalex.org/W2517464434","doi":"https://doi.org/10.1109/tsp.2018.2865434","mag":"2517464434"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2018.2865434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2018.2865434","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1608.07435","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048685188","display_name":"Henri Nurminen","orcid":"https://orcid.org/0000-0003-0949-8848"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Henri Nurminen","raw_affiliation_strings":["Tampereen yliopisto - Hervannan kampus, Tampere, Pirkanmaa, FI"],"raw_orcid":"https://orcid.org/0000-0003-0949-8848","affiliations":[{"raw_affiliation_string":"Tampereen yliopisto - Hervannan kampus, Tampere, Pirkanmaa, FI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019643618","display_name":"Tohid Ardeshiri","orcid":"https://orcid.org/0000-0003-4945-9130"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tohid Ardeshiri","raw_affiliation_strings":["University of Cambridge, Cambridge, Cambridgeshire, GB"],"raw_orcid":"https://orcid.org/0000-0003-4945-9130","affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, Cambridgeshire, GB","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002638646","display_name":"Robert Pich\u00e9","orcid":"https://orcid.org/0000-0003-1158-6951"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robert Piche","raw_affiliation_strings":["Tampereen yliopisto - Hervannan kampus, Tampere, Pirkanmaa, FI"],"raw_orcid":"https://orcid.org/0000-0003-1158-6951","affiliations":[{"raw_affiliation_string":"Tampereen yliopisto - Hervannan kampus, Tampere, Pirkanmaa, FI","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058002446","display_name":"Fredrik Gustafsson","orcid":"https://orcid.org/0000-0003-3270-171X"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Gustafsson","raw_affiliation_strings":["Linkopings universitet, Linkoping, SE"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Linkopings universitet, Linkoping, SE","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.611,"has_fulltext":true,"cited_by_count":67,"citation_normalized_percentile":{"value":0.95462515,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"66","issue":"21","first_page":"5618","last_page":"5633"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.994700014591217,"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/skew","display_name":"Skew","score":0.5996614098548889},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5659728646278381},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5238328576087952},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5122599005699158},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4948989748954773},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4742935001850128},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.44225868582725525},{"id":"https://openalex.org/keywords/skewness","display_name":"Skewness","score":0.4357765316963196},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4319063723087311},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4140251576900482},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4091659188270569},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39742857217788696},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.28159385919570923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1882394254207611},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15894082188606262}],"concepts":[{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.5996614098548889},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5659728646278381},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5238328576087952},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5122599005699158},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4948989748954773},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4742935001850128},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.44225868582725525},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.4357765316963196},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4319063723087311},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4140251576900482},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4091659188270569},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39742857217788696},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.28159385919570923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1882394254207611},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15894082188606262},{"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tsp.2018.2865434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2018.2865434","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1608.07435","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1608.07435","pdf_url":"https://arxiv.org/pdf/1608.07435","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:DiVA.org:liu-152048","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152048","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I86987016","host_organization_name":"KTH Royal Institute of Technology","host_organization_lineage":["https://openalex.org/I86987016"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:trepo.tuni.fi:10024/214289","is_oa":false,"landing_page_url":"https://trepo.tuni.fi/handle/10024/214289","pdf_url":null,"source":{"id":"https://openalex.org/S4306401860","display_name":"Tampere University Institutional Repository (Tampere University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I150589677","host_organization_name":"Tampere University of Applied Sciences","host_organization_lineage":["https://openalex.org/I150589677"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"acceptedVersion"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1608.07435","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1608.07435","pdf_url":"https://arxiv.org/pdf/1608.07435","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8299999833106995}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322426","display_name":"Nokia Foundation","ror":"https://ror.org/0401nzk46"},{"id":"https://openalex.org/F4320322591","display_name":"Tampereen Teknillinen Yliopisto","ror":"https://ror.org/02ba3pt07"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2517464434.pdf","grobid_xml":"https://content.openalex.org/works/W2517464434.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W150665491","https://openalex.org/W159361115","https://openalex.org/W1503398984","https://openalex.org/W1531532259","https://openalex.org/W1562793886","https://openalex.org/W1580282541","https://openalex.org/W1663973292","https://openalex.org/W1664060554","https://openalex.org/W1934021597","https://openalex.org/W1969682141","https://openalex.org/W1974193495","https://openalex.org/W1976718372","https://openalex.org/W1982482322","https://openalex.org/W1982914322","https://openalex.org/W2000721204","https://openalex.org/W2009086942","https://openalex.org/W2024368347","https://openalex.org/W2025634700","https://openalex.org/W2030061514","https://openalex.org/W2033076513","https://openalex.org/W2042688433","https://openalex.org/W2071818961","https://openalex.org/W2077321682","https://openalex.org/W2085069379","https://openalex.org/W2090562304","https://openalex.org/W2094227853","https://openalex.org/W2096062452","https://openalex.org/W2098439089","https://openalex.org/W2099111195","https://openalex.org/W2099867508","https://openalex.org/W2112717751","https://openalex.org/W2115979064","https://openalex.org/W2118522007","https://openalex.org/W2126736494","https://openalex.org/W2130878631","https://openalex.org/W2135401627","https://openalex.org/W2139679692","https://openalex.org/W2140050818","https://openalex.org/W2151797657","https://openalex.org/W2165077360","https://openalex.org/W2166121369","https://openalex.org/W2188789518","https://openalex.org/W2238582461","https://openalex.org/W2276280028","https://openalex.org/W2461253236","https://openalex.org/W2478708596","https://openalex.org/W2571050459","https://openalex.org/W2979752468","https://openalex.org/W3121736584","https://openalex.org/W4211128380","https://openalex.org/W4232464081","https://openalex.org/W4234686818","https://openalex.org/W4246652283","https://openalex.org/W4251400566","https://openalex.org/W4252892280","https://openalex.org/W4388085068","https://openalex.org/W6633611819","https://openalex.org/W6640231202","https://openalex.org/W6677308353","https://openalex.org/W6687005274","https://openalex.org/W6694612725"],"related_works":["https://openalex.org/W4289406402","https://openalex.org/W2896097814","https://openalex.org/W3087516072","https://openalex.org/W2502284897","https://openalex.org/W2913537149","https://openalex.org/W3082395339","https://openalex.org/W2785616772","https://openalex.org/W4315866209","https://openalex.org/W4243596578","https://openalex.org/W1622180344"],"abstract_inverted_index":{"Filtering":[0],"and":[1,27,78,86,88,95,101],"smoothing":[2],"algorithms":[3,16,133],"for":[4,159],"linear":[5],"discrete-time":[6],"state-space":[7],"models":[8],"with":[9,24],"skew-$t$-distributed":[10],"measurement":[11,143],"noise":[12,144],"are":[13],"proposed.":[14],"The":[15],"use":[17],"a":[18,59,153],"variational":[19,37,41,72],"Bayes":[20],"based":[21,103],"posterior":[22,65],"approximation":[23,62],"coupled":[25],"location":[26],"skewness":[28],"variables":[29],"to":[30,119,134],"reduce":[31],"the":[32,36,40,55,64,75,81,110,121,124,128,131,136,139,142,160],"error":[33],"caused":[34],"by":[35],"approximation.":[38],"Although":[39],"update":[42],"is":[43,145],"done":[44],"suboptimally":[45],"using":[46],"an":[47,69,116],"expectation":[48],"propagation":[49],"algorithm,":[50],"our":[51],"simulations":[52,100],"show":[53],"that":[54],"proposed":[56,71,83,132,161],"method":[57],"gives":[58],"more":[60],"accurate":[61],"of":[63,123,130,141,155],"covariance":[66],"matrix":[67],"than":[68],"earlier":[70,82],"algorithm.":[73],"Consequently,":[74],"novel":[76,125],"filter":[77,85],"smoother":[79,87],"outperform":[80],"robust":[84],"other":[89],"existing":[90],"low-complexity":[91],"alternatives":[92],"in":[93,108,115],"accuracy":[94],"speed.":[96],"We":[97],"present":[98],"both":[99],"tests":[102],"on":[104],"real-world":[105],"navigation":[106],"data,":[107],"particular":[109],"global":[111],"positioning":[112],"system":[113],"data":[114],"urban":[117],"area,":[118],"demonstrate":[120],"performance":[122,157],"methods.":[126],"Moreover,":[127],"extension":[129],"cover":[135],"case":[137],"where":[138],"distribution":[140],"multivariate":[146],"skew-$t$is":[147],"outlined.":[148],"Finally,":[149],"this":[150],"paper":[151],"presents":[152],"study":[154],"theoretical":[156],"bounds":[158],"algorithms.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-08-13T07:04:57.449891","created_date":"2025-10-10T00:00:00"}
