{"id":"https://openalex.org/W2155978838","doi":"https://doi.org/10.1109/itsc.2009.5309698","title":"Multi-target tracking for merged measurements of automotive narrow-band radar sensors","display_name":"Multi-target tracking for merged measurements of automotive narrow-band radar sensors","publication_year":2009,"publication_date":"2009-10-01","ids":{"openalex":"https://openalex.org/W2155978838","doi":"https://doi.org/10.1109/itsc.2009.5309698","mag":"2155978838"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2009.5309698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2009.5309698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 12th International IEEE Conference on Intelligent Transportation 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/A5047998113","display_name":"Sebastian Zuther","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Sebastian Zuther","raw_affiliation_strings":["Group Research & Advanced Engineering, Team Short Range Sensing, Daimler Benz Aerospace, Ulm, Germany"],"affiliations":[{"raw_affiliation_string":"Group Research & Advanced Engineering, Team Short Range Sensing, Daimler Benz Aerospace, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034719261","display_name":"Matthias Biggel","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias Biggel","raw_affiliation_strings":["Group Research & Advanced Engineering, Team Short Range Sensing, Daimler Benz Aerospace, Ulm, Germany"],"affiliations":[{"raw_affiliation_string":"Group Research & Advanced Engineering, Team Short Range Sensing, Daimler Benz Aerospace, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077859527","display_name":"Marc Muntzinger","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marc M. Muntzinger","raw_affiliation_strings":["Group Research & Advanced Engineering, Team Short Range Sensing, Daimler Benz Aerospace, Ulm, Germany"],"affiliations":[{"raw_affiliation_string":"Group Research & Advanced Engineering, Team Short Range Sensing, Daimler Benz Aerospace, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085054529","display_name":"Klaus Dietmayer","orcid":"https://orcid.org/0000-0002-1651-014X"},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus Dietmayer","raw_affiliation_strings":["Institute of Measurement, Control and Microtechnology, University of Ulm (EBS), Ulm, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Measurement, Control and Microtechnology, University of Ulm (EBS), Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047998113"],"corresponding_institution_ids":["https://openalex.org/I891521709"],"apc_list":null,"apc_paid":null,"fwci":1.3607,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.85796583,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"329","issue":null,"first_page":"1","last_page":"6"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9943000078201294,"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":0.9865999817848206,"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/computer-science","display_name":"Computer science","score":0.7130450010299683},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.6228644251823425},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6108300685882568},{"id":"https://openalex.org/keywords/monopulse-radar","display_name":"Monopulse radar","score":0.5881893634796143},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.5815010666847229},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.530903697013855},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5304103493690491},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5241442322731018},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.48820382356643677},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4211440086364746},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.41962242126464844},{"id":"https://openalex.org/keywords/radar-engineering-details","display_name":"Radar engineering details","score":0.36261382699012756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28856104612350464},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17085760831832886},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.16139638423919678},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08133649826049805}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7130450010299683},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.6228644251823425},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6108300685882568},{"id":"https://openalex.org/C186770734","wikidata":"https://www.wikidata.org/wiki/Q622911","display_name":"Monopulse radar","level":5,"score":0.5881893634796143},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.5815010666847229},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.530903697013855},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5304103493690491},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5241442322731018},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.48820382356643677},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4211440086364746},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.41962242126464844},{"id":"https://openalex.org/C134406370","wikidata":"https://www.wikidata.org/wiki/Q832005","display_name":"Radar engineering details","level":4,"score":0.36261382699012756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28856104612350464},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17085760831832886},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.16139638423919678},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08133649826049805},{"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2009.5309698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2009.5309698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 12th International IEEE Conference on Intelligent Transportation Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1576745146","https://openalex.org/W2001817222","https://openalex.org/W2011833091","https://openalex.org/W2020265997","https://openalex.org/W2097183228","https://openalex.org/W2115799376","https://openalex.org/W2120224137","https://openalex.org/W2126812776","https://openalex.org/W2153623466","https://openalex.org/W2154616225","https://openalex.org/W6682622846"],"related_works":["https://openalex.org/W2073016110","https://openalex.org/W2084270166","https://openalex.org/W2084616195","https://openalex.org/W1836016860","https://openalex.org/W1864410396","https://openalex.org/W1994593908","https://openalex.org/W2366430195","https://openalex.org/W2171702250","https://openalex.org/W3087479425","https://openalex.org/W1590237885"],"abstract_inverted_index":{"In":[0,68],"this":[1,69,84,97,124,186],"paper,":[2],"the":[3,21,30,37,44,50,111,116,137,148,161,169,174,190,194,200,219,232],"conventional":[4],"JPDAM":[5,31,51,117,220],"(joint":[6],"probabilistic":[7],"data":[8],"association":[9],"for":[10,14,61,123,199],"merged":[11,16,162],"measurements)":[12],"algorithm":[13,52,118,208,217,221],"modelling":[15],"observations,":[17],"is":[18,53,81,146,204,209],"applied":[19,130,224],"to":[20,102,168,225],"automotive":[22,73],"environment.":[23],"As":[24,49],"every":[25],"sensor":[26,80,85,213],"has":[27,86,91,119],"limited":[28,93],"resolution,":[29],"should":[32],"be":[33,129,166,183],"used":[34],"instead":[35],"of":[36,46,176,193,234],"JPDA":[38,216],"algorithm,":[39,195],"which":[40,181],"does":[41,134],"not":[42,107,128,135,165],"model":[43,136],"effects":[45],"measurement":[47,99,139,145,159,228],"merging.":[48],"more":[54,142],"complicated,":[55],"these":[56,235],"effect":[57],"are":[58,222,237],"normally":[59],"neglected":[60],"most":[62],"sensors":[63],"with":[64,157,211],"good":[65,87],"resolution":[66,94,150],"capability.":[67,95],"paper":[70],"a":[71,154,177,196,226],"new":[72],"prototypical":[74],"multi-beam":[75],"monopulse":[76],"narrow-band":[77],"FMCW":[78],"radar":[79],"used.":[82],"While":[83,115],"detection":[88],"accuracy,":[89,160],"it":[90,126,133],"only":[92],"For":[96],"sensor,":[98],"merging":[100,229],"leads":[101],"wrong":[103],"target":[104],"estimations":[105],"when":[106,141],"modelled":[108],"correctly":[109],"in":[110,147,185],"multi-target":[112],"tracking":[113],"process.":[114],"already":[120],"been":[121],"developed":[122],"case,":[125],"can":[127],"directly,":[131],"as":[132],"diminished":[138],"accuracy":[140],"than":[143],"one":[144],"same":[149],"cell.":[151],"When":[152],"using":[153],"gating":[155,179,202],"procedure":[156,203],"standard":[158],"measurements":[163],"will":[164,182],"associated":[167],"corresponding":[170],"targets.":[171],"This":[172],"motivates":[173],"usage":[175],"modified":[178,201,207],"method":[180],"presented":[184],"paper.":[187],"To":[188],"reduce":[189],"computational":[191],"demands":[192],"clustering":[197],"technique":[198],"shown.":[205],"The":[206,215],"tested":[210],"real":[212],"data.":[214],"and":[218,231],"both":[223],"challenging":[227],"scenario":[230],"results":[233],"algorithms":[236],"compared.":[238]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}
