{"id":"https://openalex.org/W2569796741","doi":"https://doi.org/10.1109/cdc.2016.7798704","title":"Fully distributed state estimation with multiple model approach","display_name":"Fully distributed state estimation with multiple model approach","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2569796741","doi":"https://doi.org/10.1109/cdc.2016.7798704","mag":"2569796741"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2016.7798704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2016.7798704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 55th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101748374","display_name":"Shaocheng Wang","orcid":"https://orcid.org/0000-0002-8094-0056"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaocheng Wang","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Riverside, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Riverside, CA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339137","display_name":"Wei Ren","orcid":"https://orcid.org/0000-0002-2818-9752"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Ren","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Riverside, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Riverside, CA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100333005","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0003-2449-9793"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Chen","raw_affiliation_strings":["State Key Laboratory of Complex System Intelligent Control and Decision, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Complex System Intelligent Control and Decision, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2920","last_page":"2925"},"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":0.9991000294685364,"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":0.9991000294685364,"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":0.9961000084877014,"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":0.9958000183105469,"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/computer-science","display_name":"Computer science","score":0.6807478666305542},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5947213768959045},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5726688504219055},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.5362811088562012},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5043817758560181},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49822020530700684},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4934753179550171},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4702892303466797},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45975613594055176},{"id":"https://openalex.org/keywords/distributed-element-model","display_name":"Distributed element model","score":0.4542868137359619},{"id":"https://openalex.org/keywords/finite-set","display_name":"Finite set","score":0.4199269413948059},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41164663434028625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24714061617851257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2014523148536682},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1562090814113617},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08000555634498596}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6807478666305542},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5947213768959045},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5726688504219055},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.5362811088562012},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5043817758560181},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49822020530700684},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4934753179550171},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4702892303466797},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45975613594055176},{"id":"https://openalex.org/C4292930","wikidata":"https://www.wikidata.org/wiki/Q17009341","display_name":"Distributed element model","level":2,"score":0.4542868137359619},{"id":"https://openalex.org/C162392398","wikidata":"https://www.wikidata.org/wiki/Q272404","display_name":"Finite set","level":2,"score":0.4199269413948059},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41164663434028625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24714061617851257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2014523148536682},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1562090814113617},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08000555634498596},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc.2016.7798704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2016.7798704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 55th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1518991729","https://openalex.org/W1531532259","https://openalex.org/W1612263467","https://openalex.org/W1963570735","https://openalex.org/W2015654594","https://openalex.org/W2024522552","https://openalex.org/W2093727232","https://openalex.org/W2116564195","https://openalex.org/W2122512809","https://openalex.org/W2129819575","https://openalex.org/W2132622054","https://openalex.org/W2132678196","https://openalex.org/W2138095955","https://openalex.org/W2140091544","https://openalex.org/W2140242774","https://openalex.org/W2145122884","https://openalex.org/W2148234182","https://openalex.org/W2153344006","https://openalex.org/W2158191982","https://openalex.org/W2159479384","https://openalex.org/W2159891802","https://openalex.org/W2160944185","https://openalex.org/W2169329579","https://openalex.org/W2247772557","https://openalex.org/W2484917588","https://openalex.org/W3100829823","https://openalex.org/W6631021461","https://openalex.org/W6679803311","https://openalex.org/W6683269704"],"related_works":["https://openalex.org/W1660242800","https://openalex.org/W2077211377","https://openalex.org/W1006270037","https://openalex.org/W3152686072","https://openalex.org/W3129238073","https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2413828414","https://openalex.org/W2367222340"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"the":[3,25,28,32,43,84,94,108,121,127,140,153,163],"problem":[4],"of":[5,31,34,51,86,110],"distributed":[6,113],"state":[7,33],"estimation":[8],"using":[9],"networked":[10],"local":[11,159],"sensors":[12],"is":[13,21,36,145,156],"studied.":[14],"Our":[15],"previously":[16],"proposed":[17,105],"algorithm":[18,81],"[1],":[19],"[2]":[20],"further":[22],"extended":[23],"to":[24,39,47,55,129],"scenario":[26],"where":[27],"underlying":[29,44,154],"model":[30,45,90,155,165],"interest":[35],"not":[37,118],"known":[38,54,71],"each":[40,134],"agent.":[41],"Instead":[42],"belongs":[46],"a":[48,66,149],"finite":[49],"set":[50],"possible":[52],"models":[53],"all":[56,158],"agents,":[57],"and":[58,100,114,137],"switches":[59],"over":[60],"time.":[61],"The":[62,104],"switching":[63],"process":[64],"follows":[65],"homogeneous":[67],"Markov":[68],"chain":[69],"with":[70],"transition":[72],"probabilities.":[73],"Two":[74],"algorithms":[75,106],"are":[76],"derived":[77],"from":[78],"our":[79],"previous":[80],"by":[82],"following":[83],"frameworks":[85],"two":[87],"well-known":[88],"multiple":[89],"(MM)":[91],"approaches,":[92],"namely,":[93],"first":[95],"order":[96],"generalized":[97],"pseudo":[98],"Bayesian":[99],"interacting":[101],"MM":[102],"approaches.":[103],"have":[107],"advantages":[109],"being":[111],"fully":[112],"robust":[115],"against":[116],"agents":[117,128,160],"directly":[119],"sensing":[120],"target.":[122],"More":[123],"importantly,":[124],"they":[125],"require":[126],"communicate":[130],"only":[131],"once":[132],"during":[133],"sampling":[135],"interval":[136],"hence":[138],"decrease":[139],"burdens":[141],"in":[142],"communication.":[143],"It":[144],"also":[146],"shown":[147],"for":[148],"special":[150],"case":[151],"when":[152],"fixed,":[157],"asymptotically":[161],"identify":[162],"true":[164],"under":[166],"certain":[167],"conditions.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
