{"id":"https://openalex.org/W3096152500","doi":"https://doi.org/10.1109/mfi49285.2020.9235266","title":"Heterogeneous Decentralized Fusion Using Conditionally Factorized Channel Filters","display_name":"Heterogeneous Decentralized Fusion Using Conditionally Factorized Channel Filters","publication_year":2020,"publication_date":"2020-09-14","ids":{"openalex":"https://openalex.org/W3096152500","doi":"https://doi.org/10.1109/mfi49285.2020.9235266","mag":"3096152500"},"language":"en","primary_location":{"id":"doi:10.1109/mfi49285.2020.9235266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi49285.2020.9235266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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/A5049423809","display_name":"Ofer Dagan","orcid":"https://orcid.org/0000-0002-2500-3887"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ofer Dagan","raw_affiliation_strings":["University of Colorado Boulder, Boulder, CO, USA"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100664008","display_name":"Nisar Ahmed","orcid":"https://orcid.org/0000-0002-7555-5671"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nisar R. Ahmed","raw_affiliation_strings":["Faculty of Aerospace Engineering, University of Colorado Boulder, Boulder, CO, USA"],"affiliations":[{"raw_affiliation_string":"Faculty of Aerospace Engineering, University of Colorado Boulder, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049423809"],"corresponding_institution_ids":["https://openalex.org/I188538660"],"apc_list":null,"apc_paid":null,"fwci":0.6628,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76434432,"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":"46","last_page":"53"},"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":0.9990000128746033,"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":0.9990000128746033,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9876999855041504,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9832000136375427,"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/conditional-independence","display_name":"Conditional independence","score":0.7199927568435669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6407155394554138},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5856390595436096},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5787906646728516},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4844358265399933},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.45934563875198364},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4300428628921509},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.4250975251197815},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4225514233112335},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.40086618065834045},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.36111634969711304},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24401065707206726},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2430378496646881},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23047885298728943},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.08029353618621826}],"concepts":[{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.7199927568435669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407155394554138},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5856390595436096},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5787906646728516},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4844358265399933},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.45934563875198364},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4300428628921509},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.4250975251197815},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4225514233112335},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40086618065834045},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.36111634969711304},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24401065707206726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2430378496646881},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23047885298728943},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.08029353618621826},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi49285.2020.9235266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi49285.2020.9235266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1538259731","https://openalex.org/W1932418203","https://openalex.org/W2030856911","https://openalex.org/W2030935194","https://openalex.org/W2040134986","https://openalex.org/W2063996629","https://openalex.org/W2090179395","https://openalex.org/W2148234182","https://openalex.org/W2159700833","https://openalex.org/W2172278910","https://openalex.org/W2219371230","https://openalex.org/W2336416123","https://openalex.org/W2507547360","https://openalex.org/W2805226549","https://openalex.org/W2898815033","https://openalex.org/W2947921054","https://openalex.org/W2968969284","https://openalex.org/W3011447944","https://openalex.org/W6683536650","https://openalex.org/W6725236576","https://openalex.org/W6774721445"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2152662039","https://openalex.org/W2726747157","https://openalex.org/W2004817612","https://openalex.org/W2010131506","https://openalex.org/W2145797872","https://openalex.org/W4226305864"],"abstract_inverted_index":{"This":[0,66],"paper":[1],"studies":[2],"a":[3,39,126,130,157],"family":[4,131],"of":[5,17,33,38,76,94,100,121,132],"heterogeneous":[6,152],"Bayesian":[7],"decentralized":[8,51],"data":[9],"fusion":[10,13],"problems.":[11],"Heterogeneous":[12],"considers":[14],"the":[15,22,25,46,61,92,98,117],"set":[16],"problems":[18,123],"in":[19,49,85],"which":[20,35],"either":[21],"communicated":[23],"or":[24],"estimated":[26],"distributions":[27],"describe":[28],"different,":[29],"but":[30],"overlapping,":[31],"states":[32,95],"interest":[34],"are":[36],"subsets":[37],"larger":[40],"full":[41,62],"global":[42,63],"joint":[43,64],"state.":[44],"On":[45],"other":[47],"hand,":[48],"homogeneous":[50],"fusion,":[52,155],"each":[53,107],"agent":[54,103],"is":[55],"required":[56],"to":[57,69,78],"process":[58],"and":[59,72,102,124,134,156],"communicate":[60],"distribution.":[65],"might":[67],"lead":[68],"high":[70],"computation":[71],"communication":[73,149],"costs":[74],"irrespective":[75],"relevancy":[77],"an":[79],"agent's":[80],"particular":[81],"mission,":[82],"for":[83,129,151],"example,":[84],"autonomous":[86],"multi-platform":[87],"multi-target":[88,158],"tracking":[89,159],"problems,":[90],"since":[91],"number":[93,99],"scales":[96],"with":[97,106],"targets":[101],"platforms,":[104],"not":[105],"agent\u2019s":[108],"specific":[109],"local":[110],"mission.":[111],"In":[112],"this":[113],"paper,":[114],"we":[115],"exploit":[116],"conditional":[118],"independence":[119],"structure":[120],"such":[122],"provide":[125,165],"rigorous":[127],"derivation":[128],"exact":[133],"approximate,":[135],"heterogeneous,":[136],"conditionally":[137],"factorized":[138],"channel":[139,153],"filter":[140,154],"methods.":[141],"Numerical":[142],"examples":[143],"show":[144],"more":[145],"than":[146],"95%":[147],"potential":[148],"reduction":[150],"simulation":[160],"shows":[161],"that":[162],"these":[163],"methods":[164],"consistent":[166],"estimates.":[167]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
