{"id":"https://openalex.org/W2889893710","doi":"https://doi.org/10.23919/icif.2018.8455436","title":"Multi-Ellipsoidal Extended Target Tracking Using Sequential Monte Carlo","display_name":"Multi-Ellipsoidal Extended Target Tracking Using Sequential Monte Carlo","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2889893710","doi":"https://doi.org/10.23919/icif.2018.8455436","mag":"2889893710"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2018.8455436","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2018.8455436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Information Fusion (FUSION)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/11511/39920","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025072392","display_name":"Suleyman Fatih Kara","orcid":"https://orcid.org/0000-0002-9155-5946"},"institutions":[{"id":"https://openalex.org/I56303344","display_name":"Aselsan (Turkey)","ror":"https://ror.org/04knh8e66","country_code":"TR","type":"company","lineage":["https://openalex.org/I56303344"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Suleyman Fatih Kara","raw_affiliation_strings":["Transportation, Security, Energy and Automation Systems Aselsan Inc., Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Transportation, Security, Energy and Automation Systems Aselsan Inc., Ankara, Turkey","institution_ids":["https://openalex.org/I56303344"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076360059","display_name":"Emre \u00d6zkan","orcid":"https://orcid.org/0000-0002-0380-2928"},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Emre Ozkan","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey","institution_ids":["https://openalex.org/I201799495"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025072392"],"corresponding_institution_ids":["https://openalex.org/I56303344"],"apc_list":null,"apc_paid":null,"fwci":0.6769,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.77757465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9901000261306763,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/ellipse","display_name":"Ellipse","score":0.6399828195571899},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6296865344047546},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5977716445922852},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5645423531532288},{"id":"https://openalex.org/keywords/ellipsoid","display_name":"Ellipsoid","score":0.521056592464447},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5107541084289551},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.4763795733451843},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.43574559688568115},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4268593192100525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3733495771884918},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36130887269973755},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31979772448539734},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3109425902366638},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.1853639781475067}],"concepts":[{"id":"https://openalex.org/C74261601","wikidata":"https://www.wikidata.org/wiki/Q40112","display_name":"Ellipse","level":2,"score":0.6399828195571899},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6296865344047546},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5977716445922852},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5645423531532288},{"id":"https://openalex.org/C57489055","wikidata":"https://www.wikidata.org/wiki/Q190046","display_name":"Ellipsoid","level":2,"score":0.521056592464447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5107541084289551},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.4763795733451843},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.43574559688568115},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4268593192100525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3733495771884918},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36130887269973755},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31979772448539734},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3109425902366638},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.1853639781475067},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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":2,"locations":[{"id":"doi:10.23919/icif.2018.8455436","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2018.8455436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Information Fusion (FUSION)","raw_type":"proceedings-article"},{"id":"pmh:oai:open.metu.edu.tr:11511/39920","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/39920","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:open.metu.edu.tr:11511/39920","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/39920","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.800000011920929,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1483307070","https://openalex.org/W1506806321","https://openalex.org/W1604155682","https://openalex.org/W1800125932","https://openalex.org/W1966447678","https://openalex.org/W2046275733","https://openalex.org/W2046579491","https://openalex.org/W2058568645","https://openalex.org/W2066624635","https://openalex.org/W2078812312","https://openalex.org/W2096678341","https://openalex.org/W2117215586","https://openalex.org/W2122469428","https://openalex.org/W2126736494","https://openalex.org/W2144598923","https://openalex.org/W2148061324","https://openalex.org/W2170790908","https://openalex.org/W2341459421","https://openalex.org/W2511369105","https://openalex.org/W2588515082","https://openalex.org/W2652334211","https://openalex.org/W2964064111","https://openalex.org/W3149903116","https://openalex.org/W6678239302"],"related_works":["https://openalex.org/W2371136327","https://openalex.org/W4293234107","https://openalex.org/W2370549269","https://openalex.org/W2386824811","https://openalex.org/W2354618530","https://openalex.org/W2081226903","https://openalex.org/W2363452175","https://openalex.org/W2520821892","https://openalex.org/W1977262557","https://openalex.org/W2375981000"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,66],"consider":[4],"the":[5,12,25,33,42,48,63,70,82,87,115,124,137],"problem":[6,50],"of":[7,69,86,123],"extended":[8],"target":[9,13,26,88,92],"tracking,":[10],"where":[11],"extent":[14,27],"cannot":[15],"be":[16],"represented":[17],"by":[18],"a":[19,59,133],"single":[20],"ellipse":[21],"accurately.":[22],"We":[23,46,108],"model":[24],"with":[28,132],"multiple":[29],"ellipses":[30],"and":[31,44,57,75,91,118],"solve":[32],"resulting":[34],"inference":[35,49],"problem,":[36],"which":[37,97],"involves":[38],"data":[39],"association":[40],"between":[41],"measurements":[43],"sub-objects.":[45],"cast":[47],"into":[51],"sequential":[52],"Monte":[53],"Carlo":[54],"(SMC)":[55],"framework":[56],"propose":[58],"simplified":[60],"approach":[61],"for":[62,100],"solution.":[64],"Furthermore,":[65],"make":[67],"use":[68,109],"Rao-Blackwellization,":[71,101],"aka":[72],"marginalization,":[73],"idea":[74],"derive":[76],"an":[77],"efficient":[78],"filter":[79],"to":[80,113],"approximate":[81,114],"joint":[83],"posterior":[84],"density":[85],"kinematic":[89],"states":[90],"extent.":[93],"Conditional":[94],"analytical":[95],"expressions,":[96],"are":[98,102],"essential":[99],"not":[103],"available":[104],"in":[105,136],"our":[106],"problem.":[107],"variational":[110],"Bayes":[111],"technique":[112],"conditional":[116],"densities":[117],"enable":[119],"Rao-Blackwellization.":[120],"The":[121],"performance":[122],"method":[125,135],"is":[126,139],"demonstrated":[127],"through":[128],"simulations.":[129],"A":[130],"comparison":[131],"recent":[134],"literature":[138],"performed.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}