{"id":"https://openalex.org/W4280590940","doi":"https://doi.org/10.1109/syscon53536.2022.9773872","title":"Comparing EKF, UKF, and PF Performance for Autonomous Vehicle Multi-Sensor Fusion and Tracking in Highway Scenario","display_name":"Comparing EKF, UKF, and PF Performance for Autonomous Vehicle Multi-Sensor Fusion and Tracking in Highway Scenario","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4280590940","doi":"https://doi.org/10.1109/syscon53536.2022.9773872"},"language":"en","primary_location":{"id":"doi:10.1109/syscon53536.2022.9773872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/syscon53536.2022.9773872","pdf_url":null,"source":{"id":"https://openalex.org/S4363608590","display_name":"2022 IEEE International Systems Conference (SysCon)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Systems Conference (SysCon)","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/A5010750654","display_name":"Kaiqiao Tian","orcid":"https://orcid.org/0000-0002-8061-615X"},"institutions":[{"id":"https://openalex.org/I177721651","display_name":"Oakland University","ror":"https://ror.org/01ythxj32","country_code":"US","type":"education","lineage":["https://openalex.org/I177721651"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kaiqiao Tian","raw_affiliation_strings":["Oakland University,Electrical and Computer Engineering,Auburn Hills,USA","Electrical and Computer Engineering, Oakland University, Auburn Hills, USA"],"affiliations":[{"raw_affiliation_string":"Oakland University,Electrical and Computer Engineering,Auburn Hills,USA","institution_ids":["https://openalex.org/I177721651"]},{"raw_affiliation_string":"Electrical and Computer Engineering, Oakland University, Auburn Hills, USA","institution_ids":["https://openalex.org/I177721651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024638263","display_name":"Micho Radovnikovich","orcid":null},"institutions":[{"id":"https://openalex.org/I177721651","display_name":"Oakland University","ror":"https://ror.org/01ythxj32","country_code":"US","type":"education","lineage":["https://openalex.org/I177721651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Micho Radovnikovich","raw_affiliation_strings":["Oakland University,Electrical and Computer Engineering,Auburn Hills,USA","Electrical and Computer Engineering, Oakland University, Auburn Hills, USA"],"affiliations":[{"raw_affiliation_string":"Oakland University,Electrical and Computer Engineering,Auburn Hills,USA","institution_ids":["https://openalex.org/I177721651"]},{"raw_affiliation_string":"Electrical and Computer Engineering, Oakland University, Auburn Hills, USA","institution_ids":["https://openalex.org/I177721651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085940760","display_name":"KaC Cheok","orcid":null},"institutions":[{"id":"https://openalex.org/I177721651","display_name":"Oakland University","ror":"https://ror.org/01ythxj32","country_code":"US","type":"education","lineage":["https://openalex.org/I177721651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"KaC Cheok","raw_affiliation_strings":["Oakland University,Electrical and Computer Engineering,Auburn Hills,USA","Electrical and Computer Engineering, Oakland University, Auburn Hills, USA"],"affiliations":[{"raw_affiliation_string":"Oakland University,Electrical and Computer Engineering,Auburn Hills,USA","institution_ids":["https://openalex.org/I177721651"]},{"raw_affiliation_string":"Electrical and Computer Engineering, Oakland University, Auburn Hills, USA","institution_ids":["https://openalex.org/I177721651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010750654"],"corresponding_institution_ids":["https://openalex.org/I177721651"],"apc_list":null,"apc_paid":null,"fwci":4.1725,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.96443173,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994000196456909,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.7882822155952454},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.709924578666687},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6875636577606201},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6548412442207336},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.6249755024909973},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5844259262084961},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.5839426517486572},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.550934374332428},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4866998493671417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47197040915489197},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4479481875896454},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.4154043197631836},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.387623131275177},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.13148686289787292},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07374650239944458},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07354176044464111}],"concepts":[{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.7882822155952454},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.709924578666687},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6875636577606201},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6548412442207336},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.6249755024909973},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5844259262084961},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.5839426517486572},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.550934374332428},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4866998493671417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47197040915489197},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4479481875896454},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.4154043197631836},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.387623131275177},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.13148686289787292},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07374650239944458},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07354176044464111},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/syscon53536.2022.9773872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/syscon53536.2022.9773872","pdf_url":null,"source":{"id":"https://openalex.org/S4363608590","display_name":"2022 IEEE International Systems Conference (SysCon)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Systems Conference (SysCon)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2011635389","https://openalex.org/W2015306524","https://openalex.org/W2050936627","https://openalex.org/W2053138020","https://openalex.org/W2082542916","https://openalex.org/W2101051269","https://openalex.org/W2134822252","https://openalex.org/W2137043637","https://openalex.org/W2145938889","https://openalex.org/W2152864241","https://openalex.org/W2163197842","https://openalex.org/W2382338163","https://openalex.org/W2564209180","https://openalex.org/W2737444374","https://openalex.org/W2756242387","https://openalex.org/W2887053799","https://openalex.org/W2959364614","https://openalex.org/W2961619538","https://openalex.org/W2973146207","https://openalex.org/W3035172746","https://openalex.org/W3040318838","https://openalex.org/W3098881644","https://openalex.org/W6678122694"],"related_works":["https://openalex.org/W4384112194","https://openalex.org/W2783354812","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W1585960250","https://openalex.org/W2341297234","https://openalex.org/W2169452249","https://openalex.org/W2378705135","https://openalex.org/W1938087941","https://openalex.org/W1582120664"],"abstract_inverted_index":{"Extended":[0],"Kalman":[1,5],"Filter":[2,6,10],"(EKF),":[3],"Unscented":[4],"(UKF),":[7],"and":[8,21,37,54,57,60,75,96,104,108,118,137,159,173,178,187,199],"Particle":[9],"(PF)":[11],"are":[12,44,185],"three":[13,116],"popular":[14],"algorithms":[15],"to":[16,83,144],"address":[17],"obstacle":[18],"position":[19,72,176],"estimate":[20,73],"tracking":[22,79,86,98,152,161],"problems.":[23],"However,":[24],"as":[25,50],"technology":[26],"develops,":[27],"autonomous":[28,113],"vehicles":[29],"pursue":[30],"a":[31,122,139,151,188],"better":[32,89],"understanding":[33],"of":[34],"the":[35,47,71,77,130],"environment":[36],"higher":[38],"safety":[39],"driving.":[40],"Different":[41],"modern":[42],"sensors":[43],"mounting":[45],"on":[46],"car,":[48],"such":[49],"three-dimensional":[51],"Light":[52],"Detection":[53,59],"Ranging":[55,61],"(LiDAR)":[56],"Radio":[58],"(Radar).":[62],"Sensor":[63],"fusion":[64,94],"from":[65],"various":[66],"data":[67,93,133,142,184],"types":[68],"can":[69,155],"improve":[70],"accuracy":[74],"challenge":[76],"traditional":[78],"algorithm.":[80],"In":[81],"order":[82],"explore":[84],"which":[85],"algorithm":[87,110,197],"has":[88],"performance":[90],"in":[91,121],"multi-sensor":[92],"(MSDF)":[95],"multi-target":[97],"(MTT)":[99],"problems,":[100],"this":[101],"paper":[102],"implements":[103],"analysis":[105],"EKF,":[106,157],"UKF,":[107,158],"PF":[109,160],"for":[111,134,171,175,196],"an":[112],"vehicle":[114],"with":[115],"LiDAR":[117,172],"two":[119],"RADAR":[120,174],"highway":[123,182],"scenario.":[124],"Our":[125],"first":[126],"contribution":[127],"is":[128,194],"processing":[129],"point":[131],"cloud":[132],"each":[135],"sensor":[136],"using":[138],"bounding":[140],"box":[141],"type":[143],"normalize":[145],"individual":[146],"obstacles.":[147],"Then":[148],"we":[149,164],"designed":[150],"system":[153],"that":[154],"switch":[156],"algorithms.":[162],"Third,":[163],"use":[165],"different":[166],"state":[167],"vector":[168],"update":[169],"matrices":[170],"updates":[177],"speed":[179],"updates.":[180],"Actual":[181],"driving":[183],"recorded,":[186],"Robotic":[189],"Operating":[190],"System":[191],"(ROS)":[192],"model":[193],"built":[195],"development":[198],"result":[200],"analysis.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
