{"id":"https://openalex.org/W3171220218","doi":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448952","title":"Adaptive Bayesian State Estimation Integrating Non-stationary DGNSS Inter-Agent Distances","display_name":"Adaptive Bayesian State Estimation Integrating Non-stationary DGNSS Inter-Agent Distances","publication_year":2021,"publication_date":"2021-04-01","ids":{"openalex":"https://openalex.org/W3171220218","doi":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448952","mag":"3171220218"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2021-spring51267.2021.9448952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","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/A5074802185","display_name":"Simone Zocca","orcid":"https://orcid.org/0000-0003-4337-673X"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Simone Zocca","raw_affiliation_strings":["Dept. of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Dept. of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043004019","display_name":"Alex Minetto","orcid":"https://orcid.org/0000-0002-0586-7151"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alex Minetto","raw_affiliation_strings":["Dept. of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Dept. of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074401924","display_name":"Fabio Dovis","orcid":"https://orcid.org/0000-0001-6078-9099"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Dovis","raw_affiliation_strings":["Dept. of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Dept. of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074802185"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":0.8158,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77764745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9894999861717224,"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/T11622","display_name":"Maritime Navigation and Safety","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/gnss-applications","display_name":"GNSS applications","score":0.7808411121368408},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.7730042338371277},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.6793318390846252},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6392547488212585},{"id":"https://openalex.org/keywords/recursive-bayesian-estimation","display_name":"Recursive Bayesian estimation","score":0.5341967940330505},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.5214440226554871},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46971458196640015},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4682620167732239},{"id":"https://openalex.org/keywords/satellite-system","display_name":"Satellite system","score":0.4654664993286133},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4551718831062317},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44834983348846436},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.42627379298210144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.293032169342041},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.2637345790863037},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.23163050413131714},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.12862563133239746},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09337800741195679}],"concepts":[{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.7808411121368408},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7730042338371277},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.6793318390846252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6392547488212585},{"id":"https://openalex.org/C40343088","wikidata":"https://www.wikidata.org/wiki/Q3059012","display_name":"Recursive Bayesian estimation","level":3,"score":0.5341967940330505},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.5214440226554871},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46971458196640015},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4682620167732239},{"id":"https://openalex.org/C2778027091","wikidata":"https://www.wikidata.org/wiki/Q25346003","display_name":"Satellite system","level":4,"score":0.4654664993286133},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4551718831062317},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44834983348846436},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.42627379298210144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.293032169342041},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.2637345790863037},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.23163050413131714},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.12862563133239746},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09337800741195679},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2021-spring51267.2021.9448952","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2021-spring51267.2021.9448952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)","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":38,"referenced_works":["https://openalex.org/W190377881","https://openalex.org/W1563108151","https://openalex.org/W1603631609","https://openalex.org/W1982733046","https://openalex.org/W2008112871","https://openalex.org/W2010529280","https://openalex.org/W2019740336","https://openalex.org/W2031398712","https://openalex.org/W2039248991","https://openalex.org/W2040196349","https://openalex.org/W2054282473","https://openalex.org/W2078808998","https://openalex.org/W2081597012","https://openalex.org/W2105281875","https://openalex.org/W2111787305","https://openalex.org/W2113731372","https://openalex.org/W2135261995","https://openalex.org/W2148863387","https://openalex.org/W2161958621","https://openalex.org/W2292367606","https://openalex.org/W2551703383","https://openalex.org/W2566918566","https://openalex.org/W2620276187","https://openalex.org/W2775432642","https://openalex.org/W2790374560","https://openalex.org/W2794124131","https://openalex.org/W2796484297","https://openalex.org/W2808576284","https://openalex.org/W2908167297","https://openalex.org/W2984817831","https://openalex.org/W2987619451","https://openalex.org/W2995221948","https://openalex.org/W3009220630","https://openalex.org/W3096387087","https://openalex.org/W3098345134","https://openalex.org/W6633794817","https://openalex.org/W6676780147","https://openalex.org/W6752100001"],"related_works":["https://openalex.org/W2606296569","https://openalex.org/W2375040471","https://openalex.org/W2068158190","https://openalex.org/W2916802843","https://openalex.org/W2064660797","https://openalex.org/W4387714868","https://openalex.org/W2071552392","https://openalex.org/W20579766","https://openalex.org/W2601478304","https://openalex.org/W4396749081"],"abstract_inverted_index":{"Bayesian":[0],"navigation":[1],"filters":[2],"are":[3,191],"broadly":[4],"exploited":[5],"in":[6,157,176],"precise":[7],"state":[8],"estimation":[9,169],"for":[10,91,101,124],"kinematic":[11],"applications":[12],"such":[13,36],"as":[14,27,37],"vehicular":[15],"positioning":[16,34],"and":[17,46],"navigation.":[18],"Among":[19],"these,":[20],"Particle":[21,127],"Filter":[22,128],"(PF)":[23],"has":[24],"been":[25],"shown":[26],"a":[28,125],"valuable":[29],"solution":[30,156],"to":[31,40,183],"support":[32],"hybrid":[33],"algorithms":[35],"sensor":[38],"fusion":[39],"Global":[41],"Navigation":[42],"Satellite":[43],"System":[44],"(GNSS)":[45],"Cooperative":[47],"Positioning":[48],"(CP).":[49],"Despite":[50],"of":[51,64,73,80,95,104,136,139,153,159,166,186],"an":[52,61,70,89,164],"increased":[53],"computational":[54],"complexity":[55],"w.r.t.":[56],"conventional":[57],"Kalman":[58],"Filters":[59],"(KFs),":[60],"effective":[62],"weighting":[63],"the":[65,74,78,81,92,96,102,133,137,140,151,154,167,174,187],"input":[66],"measurements":[67],"generally":[68],"provides":[69],"improved":[71],"accuracy":[72,170],"output":[75],"estimate.":[76],"In":[77],"framework":[79],"Differential":[82,106],"GNSS":[83,107],"(DGNSS)":[84,108],"CP,":[85],"this":[86],"work":[87],"presents":[88],"algorithm":[90],"automated":[93],"selection":[94],"most":[97],"appropriate":[98],"error":[99,160],"models":[100],"tight-integration":[103],"non-stationary":[105],"collaborative":[109],"inter-agent":[110,141],"distances.":[111],"A":[112],"model":[113,161],"switching":[114],"technique":[115],"named":[116],"Automated":[117],"Adaptive":[118],"Likelihood":[119],"Switch":[120],"(AALS)":[121],"is":[122],"proposed":[123,155],"Cognitive":[126],"(C-PF)":[129],"architecture,":[130],"based":[131],"on":[132],"real-time":[134],"approximation":[135],"statistics":[138],"distances":[142],"errors.":[143],"The":[144],"results":[145],"achieved":[146],"through":[147],"realistic":[148],"simulations":[149],"demonstrated":[150],"effectiveness":[152],"terms":[158],"selection.":[162],"Therefore,":[163],"improvement":[165],"position":[168],"was":[171],"observed,":[172],"since":[173],"cases":[175],"which":[177],"DGNSS-CP":[178],"would":[179],"degrade":[180],"performance":[181],"due":[182],"possible":[184],"mismodelling":[185],"selected":[188],"likelihood":[189],"function":[190],"avoided.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}