{"id":"https://openalex.org/W3118578253","doi":"https://doi.org/10.1109/tiv.2020.3048944","title":"Machine Learning-Based Target Classification for MMW Radar in Autonomous Driving","display_name":"Machine Learning-Based Target Classification for MMW Radar in Autonomous Driving","publication_year":2021,"publication_date":"2021-01-13","ids":{"openalex":"https://openalex.org/W3118578253","doi":"https://doi.org/10.1109/tiv.2020.3048944","mag":"3118578253"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2020.3048944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2020.3048944","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Transactions on Intelligent Vehicles","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/A5040541194","display_name":"Xiuzhang Cai","orcid":"https://orcid.org/0000-0003-1314-1892"},"institutions":[{"id":"https://openalex.org/I126452172","display_name":"Aptiv (United States)","ror":"https://ror.org/02967gp58","country_code":"US","type":"company","lineage":["https://openalex.org/I126452172","https://openalex.org/I4210107152"]},{"id":"https://openalex.org/I4210136381","display_name":"Indiana University Kokomo","ror":"https://ror.org/04161kh40","country_code":"US","type":"education","lineage":["https://openalex.org/I4210136381","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiuzhang Cai","raw_affiliation_strings":["Aptiv PLC, Kokomo, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-1314-1892","affiliations":[{"raw_affiliation_string":"Aptiv PLC, Kokomo, IN, USA","institution_ids":["https://openalex.org/I126452172","https://openalex.org/I4210136381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059370503","display_name":"Michael Giallorenzo","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Giallorenzo","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049740845","display_name":"Kamal Sarabandi","orcid":"https://orcid.org/0000-0003-2716-4622"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kamal Sarabandi","raw_affiliation_strings":["Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0003-2716-4622","affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":58.1133,"has_fulltext":false,"cited_by_count":73,"citation_normalized_percentile":{"value":0.99785523,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"6","issue":"4","first_page":"678","last_page":"689"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":0.9984999895095825,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.7453149557113647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7089382410049438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6641432642936707},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5673413872718811},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5124907493591309},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.4768720269203186},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4525463283061981},{"id":"https://openalex.org/keywords/radar-engineering-details","display_name":"Radar engineering details","score":0.44937965273857117},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42942890524864197},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3738142251968384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36340397596359253},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3552928566932678},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10339409112930298},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08611172437667847}],"concepts":[{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.7453149557113647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7089382410049438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6641432642936707},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5673413872718811},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5124907493591309},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4768720269203186},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4525463283061981},{"id":"https://openalex.org/C134406370","wikidata":"https://www.wikidata.org/wiki/Q832005","display_name":"Radar engineering details","level":4,"score":0.44937965273857117},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42942890524864197},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3738142251968384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36340397596359253},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3552928566932678},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10339409112930298},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08611172437667847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tiv.2020.3048944","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2020.3048944","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Transactions on Intelligent Vehicles","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1605443351","https://openalex.org/W1903029394","https://openalex.org/W1912918041","https://openalex.org/W1965187746","https://openalex.org/W1965723176","https://openalex.org/W1982135976","https://openalex.org/W1983361473","https://openalex.org/W1985172861","https://openalex.org/W2018543755","https://openalex.org/W2026718209","https://openalex.org/W2062684860","https://openalex.org/W2069472142","https://openalex.org/W2079537345","https://openalex.org/W2096291014","https://openalex.org/W2102605133","https://openalex.org/W2102792607","https://openalex.org/W2102882097","https://openalex.org/W2106027352","https://openalex.org/W2111917420","https://openalex.org/W2124712881","https://openalex.org/W2128934981","https://openalex.org/W2136790471","https://openalex.org/W2136849599","https://openalex.org/W2140325252","https://openalex.org/W2141790433","https://openalex.org/W2165813237","https://openalex.org/W2165978485","https://openalex.org/W2292481059","https://openalex.org/W2512479688","https://openalex.org/W2544339223","https://openalex.org/W2618530766","https://openalex.org/W2620866984","https://openalex.org/W2734871193","https://openalex.org/W2741069557","https://openalex.org/W2792919579","https://openalex.org/W2798302089","https://openalex.org/W2891649842","https://openalex.org/W2891899936","https://openalex.org/W2900240154","https://openalex.org/W2902920832","https://openalex.org/W2908760400","https://openalex.org/W2973972836","https://openalex.org/W2982458625","https://openalex.org/W4255375128","https://openalex.org/W6636135910","https://openalex.org/W6675266897"],"related_works":["https://openalex.org/W4285814362","https://openalex.org/W4352982730","https://openalex.org/W2438042271","https://openalex.org/W2027415419","https://openalex.org/W1998503825","https://openalex.org/W3207185864","https://openalex.org/W4296425733","https://openalex.org/W3127689436","https://openalex.org/W2892233029","https://openalex.org/W2309517819"],"abstract_inverted_index":{"Millimeter-wave":[0],"(MMW)":[1],"radar":[2,29,68,86,95,99,139,158],"sensors":[3,30],"are":[4,104,127,143],"considered":[5],"key":[6],"components":[7],"of":[8,12,16,47,85,193],"autonomous":[9,187],"vehicles.":[10],"Because":[11],"the":[13,50,67,130,148],"performance":[14,152],"degeneration":[15],"cameras":[17],"and":[18,35,57,70,97,114,129,153,169],"lidars":[19],"under":[20],"inclement":[21],"weather":[22],"conditions,":[23],"robust":[24],"autonomy":[25],"must":[26],"rely":[27],"on":[28,66,81],"to":[31,61,166],"perform":[32],"target":[33,39,48,71,77,140,159],"detection":[34],"classification.":[36],"Unlike":[37],"basic":[38],"classifier":[40],"methods":[41,161],"in":[42,183,189],"literature":[43],"that":[44],"make":[45],"use":[46],"velocity,":[49],"proposed":[51,131,157],"approach":[52],"is":[53,133],"far":[54,175],"more":[55],"comprehensive":[56,121],"can":[58,162],"be":[59,163],"applied":[60,164],"targets":[62],"with":[63,119,135],"zero-Doppler.":[64],"Depending":[65],"type":[69],"range,":[72],"this":[73],"paper":[74],"presents":[75],"four":[76,82],"classification":[78,102,125,141,151,160],"models":[79,103],"based":[80],"different":[83],"types":[84],"data:":[87],"statistical":[88],"RCS,":[89,92],"distributed":[90],"(time-domain)":[91],"range-azimuth":[93],"angle":[94],"images":[96],"3D":[98],"images.":[100],"The":[101,156],"implemented":[105],"by":[106],"machine":[107],"learning":[108],"approaches":[109,142],"artificial":[110],"neural":[111,116],"network":[112,117],"(ANN)":[113],"convolutional":[115],"(CNN)":[118],"a":[120,190],"simulated":[122],"dataset.":[123],"Good":[124],"accuracies":[126],"demonstrated,":[128],"model":[132],"validated":[134],"measured":[136],"data.":[137],"Different":[138],"compared,":[144],"which":[145],"clearly":[146],"reveals":[147],"trade-off":[149],"between":[150],"system":[154],"complexity.":[155],"effectively":[165],"both":[167],"static":[168],"dynamic":[170],"targets,":[171],"at":[172],"near":[173],"or":[174,179],"ranges,":[176],"using":[177],"traditional":[178],"imaging":[180],"radars,":[181],"resulting":[182],"improved":[184],"safety":[185],"for":[186],"vehicles":[188],"wide":[191],"variety":[192],"complex":[194],"environments.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}