{"id":"https://openalex.org/W2511727584","doi":"https://doi.org/10.1109/ivs.2016.7535442","title":"Multi-sensor multi-object tracking of vehicles using high-resolution radars","display_name":"Multi-sensor multi-object tracking of vehicles using high-resolution radars","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2511727584","doi":"https://doi.org/10.1109/ivs.2016.7535442","mag":"2511727584"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2016.7535442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2016.7535442","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Intelligent Vehicles Symposium (IV)","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/A5082675746","display_name":"Alexander Scheel","orcid":"https://orcid.org/0000-0002-5014-2651"},"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":true,"raw_author_name":"Alexander Scheel","raw_affiliation_strings":["Institute for Measurement, Control, and Microtechnology at Ulm University, 89081, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Measurement, Control, and Microtechnology at Ulm University, 89081, Germany","institution_ids":["https://openalex.org/I196349391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113843737","display_name":"Christina Knill","orcid":null},"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":"Christina Knill","raw_affiliation_strings":["Institue of Microwave Engineering at Ulm University, 89081, Germany"],"affiliations":[{"raw_affiliation_string":"Institue of Microwave Engineering at Ulm University, 89081, Germany","institution_ids":["https://openalex.org/I196349391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014956076","display_name":"Stephan Reuter","orcid":"https://orcid.org/0000-0002-4858-1081"},"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":"Stephan Reuter","raw_affiliation_strings":["Institute for Measurement, Control, and Microtechnology at Ulm University, 89081, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Measurement, Control, and Microtechnology at Ulm University, 89081, Germany","institution_ids":["https://openalex.org/I196349391"]}]},{"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 for Measurement, Control, and Microtechnology at Ulm University, 89081, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Measurement, Control, and Microtechnology at Ulm University, 89081, Germany","institution_ids":["https://openalex.org/I196349391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082675746"],"corresponding_institution_ids":["https://openalex.org/I196349391"],"apc_list":null,"apc_paid":null,"fwci":4.2847,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.94900958,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"558","last_page":"565"},"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":1.0,"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":1.0,"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":0.9945999979972839,"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":0.9908000230789185,"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":0.702439546585083},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.634702742099762},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.6296371817588806},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5925652980804443},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5267642736434937},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5180568695068359},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47989070415496826},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.47305622696876526},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.4534696042537689},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.44649991393089294},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.4443022310733795},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.44156742095947266},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.41945844888687134},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.41047054529190063},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.396337628364563},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.37127530574798584},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18205499649047852},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10292431712150574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.702439546585083},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.634702742099762},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.6296371817588806},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5925652980804443},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5267642736434937},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5180568695068359},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47989070415496826},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.47305622696876526},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.4534696042537689},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.44649991393089294},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.4443022310733795},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.44156742095947266},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.41945844888687134},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.41047054529190063},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.396337628364563},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.37127530574798584},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18205499649047852},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10292431712150574},{"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/ivs.2016.7535442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2016.7535442","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1909771825","https://openalex.org/W1921363914","https://openalex.org/W1959279866","https://openalex.org/W1974801345","https://openalex.org/W2026002536","https://openalex.org/W2049244691","https://openalex.org/W2056268060","https://openalex.org/W2091365726","https://openalex.org/W2110806706","https://openalex.org/W2144598923","https://openalex.org/W2149020252","https://openalex.org/W2156385851","https://openalex.org/W2165758957","https://openalex.org/W2170790908","https://openalex.org/W2516938316","https://openalex.org/W3145630061","https://openalex.org/W6639937641"],"related_works":["https://openalex.org/W2318603563","https://openalex.org/W1994458110","https://openalex.org/W2100525497","https://openalex.org/W2169452249","https://openalex.org/W887692824","https://openalex.org/W3151342408","https://openalex.org/W2354419434","https://openalex.org/W1938087941","https://openalex.org/W1582120664","https://openalex.org/W191136024"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,51,99],"automotive":[3],"radar":[4,120],"technology":[5],"have":[6],"led":[7],"to":[8,37,46,59,67],"increasing":[9],"sensor":[10],"resolution":[11],"and":[12,43,70,104],"hence":[13],"a":[14,78,100],"more":[15],"detailed":[16],"image":[17],"of":[18,73,111],"the":[19,40,56,106],"environment":[20],"with":[21],"multiple":[22,84,87],"measurements":[23],"per":[24],"object.":[25],"This":[26,92],"poses":[27],"several":[28],"challenges":[29,98],"for":[30,82],"tracking":[31,83],"systems:":[32],"new":[33],"algorithms":[34,44],"are":[35,65],"necessary":[36],"fully":[38,101],"exploit":[39],"additional":[41],"information":[42,57],"need":[45],"resolve":[47],"measurement-to-object":[48],"association":[49],"ambiguities":[50],"cluttered":[52],"multi-object":[53],"scenarios.":[54],"Also,":[55],"has":[58],"be":[60],"fused":[61],"if":[62],"multi-sensor":[63],"setups":[64],"used":[66],"obtain":[68],"redundancy":[69],"increased":[71],"fields":[72],"view.":[74],"In":[75],"this":[76],"paper,":[77],"Labeled":[79],"Multi-Bernoulli":[80],"filter":[81,94,115],"vehicles":[85],"using":[86,119],"high-resolution":[88],"radars":[89],"is":[90,105,117],"presented.":[91],"finite-set-statistics-based":[93],"tackles":[95],"all":[96],"three":[97],"probabilistic":[102],"fashion":[103],"first":[107],"Monte":[108],"Carlo":[109],"implementation":[110],"its":[112],"kind.":[113],"The":[114],"performance":[116],"evaluated":[118],"data":[121],"from":[122],"an":[123],"experimental":[124],"vehicle.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
