{"id":"https://openalex.org/W3214510201","doi":"https://doi.org/10.1109/mlsp52302.2021.9596290","title":"Bayesradar : Bayesian Metric-Kalman Filter Learning for Improved and Reliable Radar Target Classification","display_name":"Bayesradar : Bayesian Metric-Kalman Filter Learning for Improved and Reliable Radar Target Classification","publication_year":2021,"publication_date":"2021-10-25","ids":{"openalex":"https://openalex.org/W3214510201","doi":"https://doi.org/10.1109/mlsp52302.2021.9596290","mag":"3214510201"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp52302.2021.9596290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596290","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5055061318","display_name":"Anand Kumar Dubey","orcid":"https://orcid.org/0000-0001-6762-8298"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"A. Dubey","raw_affiliation_strings":["Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045725228","display_name":"Avik Santra","orcid":"https://orcid.org/0000-0002-8156-3387"},"institutions":[{"id":"https://openalex.org/I137594350","display_name":"Infineon Technologies (Germany)","ror":"https://ror.org/005kw6t15","country_code":"DE","type":"company","lineage":["https://openalex.org/I137594350"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"A. Santra","raw_affiliation_strings":["Infineon Technologies AG, Neubiberg, Germany"],"affiliations":[{"raw_affiliation_string":"Infineon Technologies AG, Neubiberg, Germany","institution_ids":["https://openalex.org/I137594350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055998127","display_name":"Jonas Fuchs","orcid":"https://orcid.org/0000-0002-4846-6374"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J. Fuchs","raw_affiliation_strings":["Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050538234","display_name":"Maximilian L\u00fcbke","orcid":"https://orcid.org/0000-0001-6527-8925"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"M. Lubke","raw_affiliation_strings":["Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070760948","display_name":"Robert Weigel","orcid":"https://orcid.org/0000-0002-3131-1800"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"R. Weigel","raw_affiliation_strings":["Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Electronics Engineering, Friedrich-Alexander-Universit\u00e4t (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072727643","display_name":"Fabian Lurz","orcid":"https://orcid.org/0000-0003-4948-9655"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]},{"id":"https://openalex.org/I884043246","display_name":"Hamburg University of Technology","ror":"https://ror.org/04bs1pb34","country_code":"DE","type":"education","lineage":["https://openalex.org/I884043246"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"F. Lurz","raw_affiliation_strings":["Institute of High-Frequency Technology, Hamburg University of Technology, Hamburg, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of High-Frequency Technology, Hamburg University of Technology, Hamburg, Germany","institution_ids":["https://openalex.org/I159176309","https://openalex.org/I884043246"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5055061318"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":0.2799,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.65526888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9979000091552734,"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":0.9979000091552734,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9864000082015991,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9786999821662903,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6985692977905273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6398503184318542},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5483690500259399},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5465268492698669},{"id":"https://openalex.org/keywords/advanced-driver-assistance-systems","display_name":"Advanced driver assistance systems","score":0.48830747604370117},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.47899362444877625},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.47474056482315063},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.46204468607902527},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4617827534675598},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4480021893978119},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.43283721804618835},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41522765159606934},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.388294517993927},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16806438565254211},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13078764081001282}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6985692977905273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6398503184318542},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5483690500259399},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5465268492698669},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.48830747604370117},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.47899362444877625},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.47474056482315063},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.46204468607902527},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4617827534675598},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4480021893978119},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.43283721804618835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41522765159606934},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.388294517993927},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16806438565254211},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13078764081001282},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/mlsp52302.2021.9596290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596290","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:tore.tuhh.de:11420/11343","is_oa":false,"landing_page_url":"http://hdl.handle.net/11420/11343","pdf_url":null,"source":{"id":"https://openalex.org/S4306401751","display_name":"tub.dok (Hamburg University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I884043246","host_organization_name":"Hamburg University of Technology","host_organization_lineage":["https://openalex.org/I884043246"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G4723255008","display_name":null,"funder_award_id":"783190","funder_id":"https://openalex.org/F4320327207","funder_display_name":"Electronic Components and Systems for European Leadership"}],"funders":[{"id":"https://openalex.org/F4320327207","display_name":"Electronic Components and Systems for European Leadership","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2005481100","https://openalex.org/W2033534992","https://openalex.org/W2245764951","https://openalex.org/W2582666574","https://openalex.org/W2600383743","https://openalex.org/W2767325013","https://openalex.org/W2791227687","https://openalex.org/W2900122153","https://openalex.org/W2973146207","https://openalex.org/W3022559717","https://openalex.org/W3157778563","https://openalex.org/W3167503326","https://openalex.org/W6735443497"],"related_works":["https://openalex.org/W1667647204","https://openalex.org/W2404647514","https://openalex.org/W4247536566","https://openalex.org/W2018477250","https://openalex.org/W3119814709","https://openalex.org/W4241418540","https://openalex.org/W1508895727","https://openalex.org/W2725786787","https://openalex.org/W1875930651","https://openalex.org/W2773753696"],"abstract_inverted_index":{"Automotive":[0],"radar":[1],"sensors":[2],"offer":[3],"a":[4,65,84,86],"promising":[5],"and":[6,11,31,40,68,124,131],"effective":[7],"modality":[8],"for":[9,102,161],"perception":[10],"assessment":[12],"of":[13,20,33,64,83,92,108,135,142,158,172],"the":[14,27,55,61,80,90,96,104,109,126,136,140,159,173],"surrounding":[15],"environment.":[16],"A":[17],"key":[18],"element":[19],"environment":[21],"sensing":[22],"in":[23,114,119,139],"automotive":[24,116],"radars":[25],"is":[26],"reliable":[28],"detection,":[29],"classification":[30,57,81,110],"tracking":[32,60,171],"vulnerable":[34,144],"road":[35,145],"users":[36,146],"such":[37],"as":[38],"pedestrians":[39],"cyclists.":[41],"In":[42],"this":[43,120],"paper,":[44,121],"we":[45,122,154],"propose":[46],"an":[47],"integrated":[48],"Bayesian":[49],"framework":[50,138],"dubbed":[51],"BayesRadar,":[52],"which":[53],"improves":[54],"overall":[56],"accuracy":[58,82],"by":[59],"embedding":[62,128,174],"vector":[63],"neural":[66],"network":[67],"its":[69],"prediction":[70],"uncertainty":[71],"via":[72],"recursive":[73],"Kalman":[74],"filtering":[75],"over":[76,95],"time.":[77],"Apart":[78],"from":[79],"model,":[85],"critical":[87],"measure":[88],"includes":[89],"analysis":[91],"statistical":[93,132],"confidence":[94,133],"target":[97],"class":[98],"score.":[99],"Such":[100],"measures":[101],"predicting":[103],"true":[105],"correctness":[106],"likelihood":[107],"estimates":[111],"are":[112],"essential":[113],"safety-critical":[115],"applications.":[117],"Therefore,":[118],"present":[123],"evaluate":[125],"classification,":[127],"cluster":[129],"score":[130],"performance":[134,157],"proposed":[137],"context":[141],"classifying":[143],"compared":[147,164],"to":[148,165],"state-of-art":[149],"deep":[150],"learning":[151],"approaches.":[152],"Furthermore,":[153],"demonstrate":[155],"superior":[156],"BayesRadar":[160],"unseen":[162],"classes":[163],"long":[166],"short-term":[167],"memory":[168],"based":[169],"temporal":[170],"vectors.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
