{"id":"https://openalex.org/W3128182865","doi":"https://doi.org/10.1109/jstsp.2021.3058062","title":"Learning-Based Extended Object Tracking Using Hierarchical Truncation Measurement Model With Automotive Radar","display_name":"Learning-Based Extended Object Tracking Using Hierarchical Truncation Measurement Model With Automotive Radar","publication_year":2021,"publication_date":"2021-02-10","ids":{"openalex":"https://openalex.org/W3128182865","doi":"https://doi.org/10.1109/jstsp.2021.3058062","mag":"3128182865"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2021.3058062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3058062","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-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/A5025858225","display_name":"Yuxuan Xia","orcid":"https://orcid.org/0000-0002-2788-7911"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Yuxuan Xia","raw_affiliation_strings":["Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383518","display_name":"Pu Wang","orcid":"https://orcid.org/0000-0002-4718-3102"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pu Wang","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090118616","display_name":"Karl Berntorp","orcid":"https://orcid.org/0000-0002-6809-6657"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karl Berntorp","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029413988","display_name":"Lennart Svensson","orcid":"https://orcid.org/0000-0003-0206-9186"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lennart Svensson","raw_affiliation_strings":["Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027594680","display_name":"Karl Granstr\u00f6m","orcid":"https://orcid.org/0000-0002-3450-988X"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Karl Granstrom","raw_affiliation_strings":["Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101648073","display_name":"Hassan Mansour","orcid":"https://orcid.org/0000-0002-1667-9885"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hassan Mansour","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034522188","display_name":"Petros T. Boufounos","orcid":"https://orcid.org/0000-0003-1369-0947"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Petros Boufounos","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044769104","display_name":"Philip V. Orlik","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip V. Orlik","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5025858225"],"corresponding_institution_ids":["https://openalex.org/I66862912"],"apc_list":null,"apc_paid":null,"fwci":5.4585,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.96376592,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"15","issue":"4","first_page":"1013","last_page":"1029"},"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":0.9779000282287598,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/radar","display_name":"Radar","score":0.6761286854743958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6097744703292847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.502943217754364},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47504448890686035},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.4716457724571228},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46885523200035095},{"id":"https://openalex.org/keywords/inverse-wishart-distribution","display_name":"Inverse-Wishart distribution","score":0.45986485481262207},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44012683629989624},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3203122019767761},{"id":"https://openalex.org/keywords/wishart-distribution","display_name":"Wishart distribution","score":0.296217679977417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20877426862716675},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.10093915462493896}],"concepts":[{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6761286854743958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6097744703292847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.502943217754364},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47504448890686035},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.4716457724571228},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46885523200035095},{"id":"https://openalex.org/C40851411","wikidata":"https://www.wikidata.org/wiki/Q3258368","display_name":"Inverse-Wishart distribution","level":4,"score":0.45986485481262207},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44012683629989624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3203122019767761},{"id":"https://openalex.org/C33962027","wikidata":"https://www.wikidata.org/wiki/Q1930697","display_name":"Wishart distribution","level":3,"score":0.296217679977417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20877426862716675},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.10093915462493896},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jstsp.2021.3058062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3058062","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:lup.lub.lu.se:dbb84c8b-bb5c-42c5-a458-9ac4598ebb39","is_oa":false,"landing_page_url":"https://lup.lub.lu.se/record/dbb84c8b-bb5c-42c5-a458-9ac4598ebb39","pdf_url":null,"source":{"id":"https://openalex.org/S4306400536","display_name":"Lund University Publications (Lund University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I187531555","host_organization_name":"Lund University","host_organization_lineage":["https://openalex.org/I187531555"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1932-4553","raw_type":"text"},{"id":"pmh:oai:research.chalmers.se:524815","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/3fb4496b-cb4b-4b6e-a0c5-5938f77e870c","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320315072","display_name":"Mitsubishi Electric Research Laboratories","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1923727756","https://openalex.org/W1966447678","https://openalex.org/W2006336681","https://openalex.org/W2007097714","https://openalex.org/W2018275473","https://openalex.org/W2040104067","https://openalex.org/W2056268060","https://openalex.org/W2058568645","https://openalex.org/W2078812312","https://openalex.org/W2085738358","https://openalex.org/W2101234009","https://openalex.org/W2140242774","https://openalex.org/W2144598923","https://openalex.org/W2151840198","https://openalex.org/W2319030420","https://openalex.org/W2341459421","https://openalex.org/W2513434274","https://openalex.org/W2516938316","https://openalex.org/W2588070846","https://openalex.org/W2588927596","https://openalex.org/W2616349869","https://openalex.org/W2737128717","https://openalex.org/W2771901986","https://openalex.org/W2791344335","https://openalex.org/W2801573735","https://openalex.org/W2891185125","https://openalex.org/W2891822104","https://openalex.org/W2892055118","https://openalex.org/W2904296639","https://openalex.org/W2931912698","https://openalex.org/W2948034885","https://openalex.org/W2963194653","https://openalex.org/W2964064111","https://openalex.org/W3010708856","https://openalex.org/W3012381239","https://openalex.org/W3014510953","https://openalex.org/W3015904121","https://openalex.org/W3034362563","https://openalex.org/W3035574168","https://openalex.org/W3038010327","https://openalex.org/W3040360205","https://openalex.org/W3101735304","https://openalex.org/W3112694273","https://openalex.org/W4241181106","https://openalex.org/W6640216750","https://openalex.org/W6675354045","https://openalex.org/W6682264089","https://openalex.org/W6760592408","https://openalex.org/W6774789169","https://openalex.org/W6787447852"],"related_works":["https://openalex.org/W1891287906","https://openalex.org/W2036807459","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W2755342338","https://openalex.org/W1984405384","https://openalex.org/W2133017515","https://openalex.org/W2016711537"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,26,95,110,122],"data-driven":[4],"measurement":[5,45,89,104],"model":[6,46,71,78,90],"for":[7],"extended":[8],"object":[9],"tracking":[10],"(EOT)":[11],"with":[12,31,101],"automotive":[13,20,57],"radar.":[14],"Specifically,":[15],"the":[16,40,52,69,75,82,117,130],"spatial":[17,53],"distribution":[18,54],"of":[19,55,129],"radar":[21,58,62],"measurements":[22],"is":[23,91,107,119,133],"modeled":[24],"as":[25],"hierarchical":[27],"truncated":[28],"Gaussian":[29,112],"(HTG)":[30],"structural":[32],"geometry":[33],"parameters":[34,72],"that":[35],"can":[36,64],"be":[37,65],"learned":[38,87],"from":[39,81],"training":[41],"data.":[42],"The":[43,86,127],"HTG":[44,88],"provides":[47],"an":[48],"adequate":[49],"resemblance":[50],"to":[51,67],"real-world":[56,140],"measurements.":[59],"Moreover,":[60],"large-scale":[61],"datasets":[63],"leveraged":[66],"learn":[68],"geometry-related":[70],"and":[73,116,139],"offload":[74],"computationally":[76],"demanding":[77],"parameter":[79],"estimation":[80],"state":[83],"update":[84],"step.":[85],"further":[92],"incorporated":[93],"into":[94],"random":[96],"matrix":[97],"based":[98,108,120],"EOT":[99],"approach":[100],"two":[102],"(multi-sensor)":[103],"updates:":[105],"one":[106],"on":[109,121,135],"factorized":[111],"inverse-Wishart":[113],"density":[114,125],"representation":[115],"other":[118],"Rao-Blackwellized":[123],"particle":[124],"representation.":[126],"effectiveness":[128],"proposed":[131],"approaches":[132],"verified":[134],"both":[136],"synthetic":[137],"data":[138],"nuScenes":[141],"dataset":[142],"over":[143],"300":[144],"trajectories.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}