{"id":"https://openalex.org/W2135363148","doi":"https://doi.org/10.1109/mfi.2008.4648063","title":"A comparison of track-to-track fusion algorithms for automotive sensor fusion","display_name":"A comparison of track-to-track fusion algorithms for automotive sensor fusion","publication_year":2008,"publication_date":"2008-08-01","ids":{"openalex":"https://openalex.org/W2135363148","doi":"https://doi.org/10.1109/mfi.2008.4648063","mag":"2135363148"},"language":"en","primary_location":{"id":"doi:10.1109/mfi.2008.4648063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2008.4648063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems","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/A5032302693","display_name":"Stephan Matzka","orcid":"https://orcid.org/0000-0002-3458-5786"},"institutions":[{"id":"https://openalex.org/I4210106192","display_name":"Technische Hochschule Ingolstadt","ror":"https://ror.org/02bxzcy64","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210106192"]},{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["DE","GB"],"is_corresponding":true,"raw_author_name":"Stephan Matzka","raw_affiliation_strings":["Heriot-Watt University, Edinburgh, United Kingdom","Heriot-Watt University, Edinburgh, UK","Institute for Applied Research, Ingolstadt University of Applied Sciences, Ingolstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I32062511"]},{"raw_affiliation_string":"Heriot-Watt University, Edinburgh, UK","institution_ids":["https://openalex.org/I32062511"]},{"raw_affiliation_string":"Institute for Applied Research, Ingolstadt University of Applied Sciences, Ingolstadt, Germany","institution_ids":["https://openalex.org/I4210106192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014546472","display_name":"Richard Altendorfer","orcid":"https://orcid.org/0000-0003-2884-8444"},"institutions":[{"id":"https://openalex.org/I4210115888","display_name":"TRW Automotive (Germany)","ror":"https://ror.org/02j8awh30","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210115888","https://openalex.org/I887702905"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Richard Altendorfer","raw_affiliation_strings":["TRW Automotive, 56070 Koblenz, Germany","TRW Automotive, Koblenz, Germany"],"affiliations":[{"raw_affiliation_string":"TRW Automotive, 56070 Koblenz, Germany","institution_ids":["https://openalex.org/I4210115888"]},{"raw_affiliation_string":"TRW Automotive, Koblenz, Germany","institution_ids":["https://openalex.org/I4210115888"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032302693"],"corresponding_institution_ids":["https://openalex.org/I32062511","https://openalex.org/I4210106192"],"apc_list":null,"apc_paid":null,"fwci":4.6831,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":{"value":0.94698359,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"189","last_page":"194"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9624000191688538,"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":0.9584000110626221,"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/covariance-intersection","display_name":"Covariance intersection","score":0.9662303328514099},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.7909114360809326},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.7614846229553223},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.7314807772636414},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5922802090644836},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5892226696014404},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.525691032409668},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5075739622116089},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.4570264518260956},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.42478081583976746},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35742253065109253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3324858546257019},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22498050332069397},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21441403031349182},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12264630198478699}],"concepts":[{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.9662303328514099},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7909114360809326},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.7614846229553223},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7314807772636414},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5922802090644836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5892226696014404},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.525691032409668},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5075739622116089},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.4570264518260956},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42478081583976746},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35742253065109253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3324858546257019},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22498050332069397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21441403031349182},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12264630198478699},{"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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mfi.2008.4648063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2008.4648063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.140.4992","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.4992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.bkfc.net/altendor/MFI2008.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W7309667","https://openalex.org/W304861154","https://openalex.org/W1568122762","https://openalex.org/W2006832107","https://openalex.org/W2055762251","https://openalex.org/W2095323263","https://openalex.org/W2129078811","https://openalex.org/W2139412680","https://openalex.org/W2140242774","https://openalex.org/W2147761571","https://openalex.org/W6681872261"],"related_works":["https://openalex.org/W2509635936","https://openalex.org/W2952184814","https://openalex.org/W2718384077","https://openalex.org/W4411451922","https://openalex.org/W1597192237","https://openalex.org/W2525877954","https://openalex.org/W2022823194","https://openalex.org/W2317323511","https://openalex.org/W2103062922","https://openalex.org/W2543883930"],"abstract_inverted_index":{"In":[0],"exteroceptive":[1],"automotive":[2],"sensor":[3,5,20,46,66,76],"fusion,":[4],"data":[6,15,28,47,67],"are":[7],"usually":[8],"only":[9],"available":[10],"as":[11,18,48,50],"processed,":[12],"tracked":[13,65],"object":[14],"and":[16,33,86,100],"not":[17],"raw":[19],"data.":[21],"Applying":[22],"a":[23,58,112,116],"Kalman":[24,61,113],"filter":[25,62,114],"to":[26,30,41,64,68,106],"such":[27],"leads":[29],"additional":[31],"delays":[32],"generally":[34],"underestimates":[35],"the":[36,55,72,91],"fused":[37],"objectspsila":[38],"covariance":[39,82,84,98],"due":[40],"temporal":[42],"correlations":[43],"of":[44,57,75,78,88,102],"individual":[45],"well":[49],"inter-sensor":[51],"correlations.":[52],"We":[53],"compare":[54],"performance":[56],"standard":[59],"asynchronous":[60],"applied":[63],"several":[69],"algorithms":[70],"for":[71],"track-to-track":[73],"fusion":[74],"objects":[77],"unknown":[79],"correlation,":[80],"namely":[81],"union,":[83],"intersection,":[85],"use":[87,101],"cross-covariance.":[89],"For":[90],"simulation":[92],"setup":[93],"used":[94],"in":[95],"this":[96],"paper,":[97],"intersection":[99],"cross-covariance":[103],"turn":[104],"out":[105],"yield":[107],"significantly":[108],"lower":[109],"errors":[110],"than":[111],"at":[115],"comparable":[117],"computational":[118],"load.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
