{"id":"https://openalex.org/W3116621361","doi":"https://doi.org/10.1109/tvt.2020.3047107","title":"Robust Poisson Multi-Bernoulli Mixture Filter With Unknown Detection Probability","display_name":"Robust Poisson Multi-Bernoulli Mixture Filter With Unknown Detection Probability","publication_year":2020,"publication_date":"2020-12-24","ids":{"openalex":"https://openalex.org/W3116621361","doi":"https://doi.org/10.1109/tvt.2020.3047107","mag":"3116621361"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2020.3047107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.3047107","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5069239821","display_name":"Guchong Li","orcid":"https://orcid.org/0000-0002-9182-1968"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guchong Li","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022778463","display_name":"Lingjiang Kong","orcid":"https://orcid.org/0000-0002-0991-4517"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjiang Kong","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339151","display_name":"Wei Yi","orcid":"https://orcid.org/0000-0001-9878-7048"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Yi","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100371547","display_name":"Xiaolong Li","orcid":"https://orcid.org/0000-0002-5712-8772"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Li","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069239821"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":2.721,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.92278193,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"70","issue":"1","first_page":"886","last_page":"899"},"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":0.9864000082015991,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9812999963760376,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bernoullis-principle","display_name":"Bernoulli's principle","score":0.7048583626747131},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.6860901713371277},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6481321454048157},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6343364715576172},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5003175735473633},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48118287324905396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47963032126426697},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.4775082468986511},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.46354907751083374},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.4510972201824188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.424740731716156},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32022958993911743},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24654117226600647},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17941692471504211},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.11644178628921509},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10109126567840576}],"concepts":[{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.7048583626747131},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.6860901713371277},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6481321454048157},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6343364715576172},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5003175735473633},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48118287324905396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47963032126426697},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.4775082468986511},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.46354907751083374},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.4510972201824188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.424740731716156},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32022958993911743},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24654117226600647},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17941692471504211},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.11644178628921509},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10109126567840576},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2020.3047107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.3047107","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4226010120","display_name":null,"funder_award_id":"61\u00a0771\u00a0110","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8978917354","display_name":null,"funder_award_id":"B17008","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W34992941","https://openalex.org/W652333456","https://openalex.org/W1531532259","https://openalex.org/W1557595030","https://openalex.org/W1568122762","https://openalex.org/W1579369571","https://openalex.org/W1909771825","https://openalex.org/W1965449873","https://openalex.org/W1979348982","https://openalex.org/W1985621395","https://openalex.org/W2001691743","https://openalex.org/W2011087880","https://openalex.org/W2014787937","https://openalex.org/W2015083454","https://openalex.org/W2023516725","https://openalex.org/W2049244691","https://openalex.org/W2105905583","https://openalex.org/W2110012495","https://openalex.org/W2110354007","https://openalex.org/W2120378065","https://openalex.org/W2122512809","https://openalex.org/W2123378338","https://openalex.org/W2123487311","https://openalex.org/W2126885789","https://openalex.org/W2129570991","https://openalex.org/W2137585588","https://openalex.org/W2144617132","https://openalex.org/W2154353836","https://openalex.org/W2156163297","https://openalex.org/W2161435744","https://openalex.org/W2170414118","https://openalex.org/W2294153305","https://openalex.org/W2296664252","https://openalex.org/W2424916488","https://openalex.org/W2507805920","https://openalex.org/W2515891673","https://openalex.org/W2571050459","https://openalex.org/W2594299295","https://openalex.org/W2595600061","https://openalex.org/W2623681295","https://openalex.org/W2742210669","https://openalex.org/W2801422522","https://openalex.org/W2824536815","https://openalex.org/W2913213964","https://openalex.org/W2932520762","https://openalex.org/W2948034885","https://openalex.org/W2964060597","https://openalex.org/W2969740029","https://openalex.org/W2970258442","https://openalex.org/W2970613990","https://openalex.org/W2979653692","https://openalex.org/W3008383159","https://openalex.org/W3012318425","https://openalex.org/W3083908220","https://openalex.org/W3084747182","https://openalex.org/W3098020076","https://openalex.org/W3100903055","https://openalex.org/W3101703006","https://openalex.org/W3101735304","https://openalex.org/W3102355812","https://openalex.org/W3187867541","https://openalex.org/W4254248308","https://openalex.org/W6633511732","https://openalex.org/W6725276814","https://openalex.org/W6726484312","https://openalex.org/W6761155568"],"related_works":["https://openalex.org/W2002177687","https://openalex.org/W2058438338","https://openalex.org/W2019471580","https://openalex.org/W1619264321","https://openalex.org/W2941284322","https://openalex.org/W4224920876","https://openalex.org/W2168299207","https://openalex.org/W2061675390","https://openalex.org/W1967524736","https://openalex.org/W3011535717"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,17,66,77,124,135],"robust":[4],"Poisson":[5,118],"multi-Bernoulli":[6],"mixture":[7,126],"(R-PMBM)":[8],"filter":[9],"immune":[10],"to":[11,105,123,134],"the":[12,22,37,68,73,85,90,98,102,106,115,145,150],"unknown":[13],"detection":[14,26,74,91],"probability.":[15],"In":[16,40],"majority":[18],"of":[19,25,63,70,113,117,131,149],"multi-object":[20],"scenarios,":[21],"prior":[23],"knowledge":[24],"probability":[27,75,92],"is":[28,32,45,79],"usually":[29],"uncertain,":[30],"which":[31],"often":[33],"estimated":[34,95],"offline":[35],"from":[36],"training":[38],"data.":[39],"such":[41],"cases,":[42],"online":[43],"filtering":[44],"always":[46],"unfeasible":[47],"or":[48],"unrealistic,":[49],"otherwise,":[50],"significant":[51],"parameter":[52],"mismatches":[53],"will":[54],"result":[55],"in":[56,81],"biased":[57],"estimates":[58],"(e.g.,":[59],"state":[60,99],"and":[61,129,147],"cardinality":[62],"objects).":[64],"As":[65],"consequence,":[67],"ability":[69],"adaptively":[71],"estimating":[72],"for":[76],"sensor":[78],"essential":[80],"practice.":[82],"Based":[83],"on":[84],"analysis,":[86],"we":[87],"detail":[88],"how":[89],"can":[93],"be":[94],"accompanied":[96],"with":[97],"estimates.":[100],"Besides,":[101],"closed-form":[103],"solutions":[104],"proposed":[107,151],"method":[108],"are":[109],"derived":[110],"by":[111],"means":[112],"approximating":[114],"intensity":[116],"random":[119],"finite":[120],"set":[121],"(RFS)":[122],"Beta-Gaussian":[125,137],"(BGM)":[127],"form":[128],"density":[130],"Bernoulli":[132],"RFS":[133],"single":[136],"form,":[138],"named":[139],"BGM-PMBM":[140],"filter.":[141],"Simulation":[142],"results":[143],"demonstrate":[144],"effectiveness":[146],"robustness":[148],"method.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}