{"id":"https://openalex.org/W2594299295","doi":"https://doi.org/10.1109/tsp.2017.2675866","title":"Poisson Multi-Bernoulli Mapping Using Gibbs Sampling","display_name":"Poisson Multi-Bernoulli Mapping Using Gibbs Sampling","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2594299295","doi":"https://doi.org/10.1109/tsp.2017.2675866","mag":"2594299295"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2017.2675866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2675866","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/1811.03154","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103234186","display_name":"Maryam Fatemi","orcid":"https://orcid.org/0000-0002-9141-5994"},"institutions":[{"id":"https://openalex.org/I109556086","display_name":"Autoliv (Sweden)","ror":"https://ror.org/01jy49h31","country_code":"SE","type":"company","lineage":["https://openalex.org/I109556086"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Maryam Fatemi","raw_affiliation_strings":["Department of Signals and Systems, Autoliv Sverige AB, V\u00e5rg\u00e5rda, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signals and Systems, Autoliv Sverige AB, V\u00e5rg\u00e5rda, Sweden","institution_ids":["https://openalex.org/I109556086"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027594680","display_name":"Karl Granstr\u00f6m","orcid":"https://orcid.org/0000-0002-3450-988X"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Karl Granstrom","raw_affiliation_strings":["Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029413988","display_name":"Lennart Svensson","orcid":"https://orcid.org/0000-0003-0206-9186"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lennart Svensson","raw_affiliation_strings":["Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101992030","display_name":"Francisco J. R. Ruiz","orcid":"https://orcid.org/0000-0002-2200-901X"},"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"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Francisco J. R. Ruiz","raw_affiliation_strings":["Computer Science Department, Columbia University, New York, NY, USA","Department of Engineering, University of Cambridge, Cambridge, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Engineering, University of Cambridge, Cambridge, U.K","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035123040","display_name":"Lars Hammarstrand","orcid":null},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lars Hammarstrand","raw_affiliation_strings":["Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.5827,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.96618709,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"65","issue":"11","first_page":"2814","last_page":"2827"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9986000061035156,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9986000061035156,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9955000281333923,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9452000260353088,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.6666167974472046},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.6351735591888428},{"id":"https://openalex.org/keywords/bernoullis-principle","display_name":"Bernoulli's principle","score":0.579750120639801},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.5522133708000183},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5242460370063782},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4711792767047882},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45982953906059265},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.41624826192855835},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3372325301170349},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3260710835456848},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1823478639125824},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.16837522387504578},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13593599200248718},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1319621205329895}],"concepts":[{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.6666167974472046},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.6351735591888428},{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.579750120639801},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.5522133708000183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5242460370063782},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4711792767047882},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45982953906059265},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.41624826192855835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3372325301170349},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3260710835456848},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1823478639125824},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.16837522387504578},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13593599200248718},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1319621205329895},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tsp.2017.2675866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2017.2675866","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:1811.03154","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.03154","pdf_url":"https://arxiv.org/pdf/1811.03154","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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:generic.eprints.org:1034530","is_oa":false,"landing_page_url":"http://publications.eng.cam.ac.uk/1034530/","pdf_url":null,"source":{"id":"https://openalex.org/S4406922847","display_name":"Cambridge University Engineering Department Publications Database","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:publications.lib.chalmers.se:249608","is_oa":false,"landing_page_url":"http://publications.lib.chalmers.se/publication/249608-poisson-multi-bernoulli-mapping-using-gibbs-sampling","pdf_url":null,"source":{"id":"https://openalex.org/S4377196470","display_name":"Chalmers Publication Library (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text.Article.Journal.PeerReviewed"},{"id":"pmh:oai:research.chalmers.se:249608","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/249608","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1811.03154","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.03154","pdf_url":"https://arxiv.org/pdf/1811.03154","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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","score":0.6700000166893005,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G5173174905","display_name":null,"funder_award_id":"N00014-11-1-0651","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G674193418","display_name":null,"funder_award_id":"706760","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G7331901853","display_name":null,"funder_award_id":"EU H2020","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W34992941","https://openalex.org/W43029633","https://openalex.org/W748467075","https://openalex.org/W1496856925","https://openalex.org/W1516111018","https://openalex.org/W1709455389","https://openalex.org/W1965555277","https://openalex.org/W1985093013","https://openalex.org/W1990012555","https://openalex.org/W1993235647","https://openalex.org/W2014787937","https://openalex.org/W2018275473","https://openalex.org/W2020324514","https://openalex.org/W2032924574","https://openalex.org/W2044343239","https://openalex.org/W2053405531","https://openalex.org/W2069429561","https://openalex.org/W2069739265","https://openalex.org/W2077969890","https://openalex.org/W2078762661","https://openalex.org/W2080823437","https://openalex.org/W2080972498","https://openalex.org/W2094728544","https://openalex.org/W2097355360","https://openalex.org/W2104396692","https://openalex.org/W2108288396","https://openalex.org/W2110012495","https://openalex.org/W2115870554","https://openalex.org/W2115979064","https://openalex.org/W2120340025","https://openalex.org/W2127578024","https://openalex.org/W2143864104","https://openalex.org/W2144598923","https://openalex.org/W2146881125","https://openalex.org/W2148820580","https://openalex.org/W2148919666","https://openalex.org/W2156385851","https://openalex.org/W2160320341","https://openalex.org/W2270755773","https://openalex.org/W2400776833","https://openalex.org/W2474005181","https://openalex.org/W2491497334","https://openalex.org/W2514570524","https://openalex.org/W2948034885","https://openalex.org/W3143528639","https://openalex.org/W3145630061","https://openalex.org/W4230436525","https://openalex.org/W4237780050","https://openalex.org/W4237840503","https://openalex.org/W4256542144","https://openalex.org/W4292403327","https://openalex.org/W4293052541","https://openalex.org/W4308951891","https://openalex.org/W6629759753","https://openalex.org/W6648473370","https://openalex.org/W6674849818","https://openalex.org/W6676085441","https://openalex.org/W6677308353","https://openalex.org/W6682324061","https://openalex.org/W6683366892"],"related_works":["https://openalex.org/W2002177687","https://openalex.org/W3146360815","https://openalex.org/W2058438338","https://openalex.org/W2019471580","https://openalex.org/W1619264321","https://openalex.org/W2941284322","https://openalex.org/W4224920876","https://openalex.org/W2061675390","https://openalex.org/W1967524736","https://openalex.org/W3011535717"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,13,21,31,39,49,58,63,82,93,97,100,116],"mapping":[4],"problem.":[5],"Using":[6],"a":[7,24,44,53,67,75,129],"conjugate":[8],"prior":[9,56],"form,":[10],"we":[11],"derive":[12],"exact":[14],"theoretical":[15],"batch":[16,83],"multiobject":[17,84],"posterior":[18,64],"density":[19],"of":[20,26,99,102,115],"map":[22,32,59],"given":[23],"set":[25,101],"measurements.":[27],"The":[28,86,113],"landmarks":[29],"in":[30,92],"are":[33,41],"modeled":[34],"as":[35,43],"extended":[36],"objects,":[37],"and":[38,60,96,104,124],"measurements":[40],"described":[42],"Poisson":[45,54],"process,":[46],"conditioned":[47],"on":[48,57,121],"map.":[50],"We":[51,73],"use":[52],"process":[55],"prove":[61],"that":[62],"distribution":[65],"is":[66,105,119,125],"hybrid":[68],"Poisson,":[69],"multi-Bernoulli":[70],"mixture":[71],"distribution.":[72],"devise":[74],"Gibbs":[76],"sampling":[77],"algorithm":[78],"to":[79,127],"sample":[80],"from":[81],"posterior.":[85],"proposed":[87,117],"method":[88,118],"can":[89],"handle":[90],"uncertainties":[91],"data":[94,123],"associations":[95],"cardinality":[98],"landmarks,":[103],"parallelizable,":[106],"making":[107],"it":[108],"suitable":[109],"for":[110],"large-scale":[111],"problems.":[112],"performance":[114],"evaluated":[120],"synthetic":[122],"shown":[126],"outperform":[128],"state-of-the-art":[130],"method.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
