{"id":"https://openalex.org/W4318624526","doi":"https://doi.org/10.1109/tvt.2023.3240740","title":"Road-Map Aided Gaussian Mixture Labeled Multi-Bernoulli Filter for Ground Multi- Target Tracking","display_name":"Road-Map Aided Gaussian Mixture Labeled Multi-Bernoulli Filter for Ground Multi- Target Tracking","publication_year":2023,"publication_date":"2023-01-31","ids":{"openalex":"https://openalex.org/W4318624526","doi":"https://doi.org/10.1109/tvt.2023.3240740"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2023.3240740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3240740","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5012567101","display_name":"Chaoqun Yang","orcid":"https://orcid.org/0000-0002-5081-5537"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoqun Yang","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5081-5537","affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085757528","display_name":"Xianghui Cao","orcid":"https://orcid.org/0000-0002-6771-0571"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghui Cao","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-6771-0571","affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041940889","display_name":"Zhiguo Shi","orcid":"https://orcid.org/0000-0001-9160-048X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiguo Shi","raw_affiliation_strings":["College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9160-048X","affiliations":[{"raw_affiliation_string":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5169,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.9095811,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"72","issue":"6","first_page":"7137","last_page":"7147"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9907000064849854,"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"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.989799976348877,"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/clutter","display_name":"Clutter","score":0.7906231880187988},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6432793736457825},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6354173421859741},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6297574639320374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6064344644546509},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5348706841468811},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.48721736669540405},{"id":"https://openalex.org/keywords/moving-target-indication","display_name":"Moving target indication","score":0.4581976532936096},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.4432506859302521},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.44036397337913513},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.4123240113258362},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36133241653442383},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3330910801887512},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.2596428394317627},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1932639181613922},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11839613318443298},{"id":"https://openalex.org/keywords/continuous-wave-radar","display_name":"Continuous-wave radar","score":0.11776521801948547},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09743231534957886}],"concepts":[{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7906231880187988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6432793736457825},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6354173421859741},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6297574639320374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6064344644546509},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5348706841468811},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.48721736669540405},{"id":"https://openalex.org/C162416716","wikidata":"https://www.wikidata.org/wiki/Q446180","display_name":"Moving target indication","level":5,"score":0.4581976532936096},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.4432506859302521},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.44036397337913513},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.4123240113258362},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36133241653442383},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3330910801887512},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.2596428394317627},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1932639181613922},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11839613318443298},{"id":"https://openalex.org/C59584813","wikidata":"https://www.wikidata.org/wiki/Q1029234","display_name":"Continuous-wave radar","level":4,"score":0.11776521801948547},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09743231534957886},{"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2023.3240740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3240740","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G6719098709","display_name":null,"funder_award_id":"92067111","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7121147207","display_name":null,"funder_award_id":"BK20202006","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G7418535098","display_name":null,"funder_award_id":"61973163","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1909771825","https://openalex.org/W2049244691","https://openalex.org/W2052701631","https://openalex.org/W2106873007","https://openalex.org/W2126885789","https://openalex.org/W2134466075","https://openalex.org/W2153416300","https://openalex.org/W2154353836","https://openalex.org/W2319114554","https://openalex.org/W2595600061","https://openalex.org/W2616555170","https://openalex.org/W2743556323","https://openalex.org/W2790002497","https://openalex.org/W2824536815","https://openalex.org/W2888106621","https://openalex.org/W2892433162","https://openalex.org/W2898521547","https://openalex.org/W2904147910","https://openalex.org/W2926807184","https://openalex.org/W2945329049","https://openalex.org/W2945895672","https://openalex.org/W2964700183","https://openalex.org/W2967354244","https://openalex.org/W2973169463","https://openalex.org/W2989101914","https://openalex.org/W3007456408","https://openalex.org/W3008383159","https://openalex.org/W3013404017","https://openalex.org/W3032938961","https://openalex.org/W3081796926","https://openalex.org/W3102355812","https://openalex.org/W3156482771","https://openalex.org/W3168756155","https://openalex.org/W3197686404","https://openalex.org/W3200340927","https://openalex.org/W3204847413","https://openalex.org/W3216673499","https://openalex.org/W4213417732","https://openalex.org/W4237817353"],"related_works":["https://openalex.org/W2230756318","https://openalex.org/W2060933360","https://openalex.org/W4287877599","https://openalex.org/W2114489213","https://openalex.org/W1905797650","https://openalex.org/W254936539","https://openalex.org/W2027218115","https://openalex.org/W2792978743","https://openalex.org/W2390483201","https://openalex.org/W1962885721"],"abstract_inverted_index":{"Ground":[0],"multi-target":[1],"tracking":[2,49],"(MTT)":[3],"is":[4],"one":[5],"of":[6,10,107],"the":[7,48,78,105,113,118,123,139,144],"core":[8],"tasks":[9],"airborne":[11],"ground":[12,22,52],"moving":[13],"target":[14],"indicator":[15],"(GMTI)":[16],"radar":[17],"and":[18,91,134],"automotive":[19],"radar.":[20],"However,":[21],"MTT":[23],"still":[24],"remains":[25],"a":[26,60,87],"challenging":[27],"issue":[28],"especially":[29],"in":[30,55,104],"complex":[31],"traffic":[32],"scenarios,":[33],"since":[34],"it":[35],"often":[36],"suffers":[37],"from":[38],"high":[39],"clutter,":[40],"dense":[41],"targets,":[42,54],"low":[43],"visibility,":[44],"etc.":[45],"To":[46],"enhance":[47],"performance":[50],"for":[51],"multiple":[53],"this":[56],"paper,":[57],"we":[58,84,111],"present":[59],"comprehensive":[61],"solution":[62],"named":[63],"road-map":[64,75,98,108,120],"aided":[65],"Gaussian":[66,127],"mixture":[67,128],"labeled":[68,79],"multi-Bernoulli":[69,80],"filter":[70,115,125,142],"(RA-GMLMB)":[71],"filter,":[72],"which":[73,100],"incorporates":[74],"information":[76,121],"into":[77,122],"(LMB)":[81],"filter.":[82],"Specifically,":[83],"first":[85],"propose":[86],"hybrid":[88],"circular":[89],"arc":[90],"line":[92],"segments":[93],"approximation":[94,102],"approach":[95],"to":[96],"extract":[97],"information,":[99],"alleviates":[101],"errors":[103],"procedure":[106],"approximation.":[109],"Then,":[110],"deduce":[112],"RA-GMLMB":[114,141],"by":[116],"integrating":[117],"extracted":[119],"LMB":[124],"with":[126],"implementation.":[129],"Simulation":[130],"experiments":[131],"are":[132],"conducted":[133],"experimental":[135],"results":[136],"show":[137],"that":[138],"proposed":[140],"outperforms":[143],"state-of-the-art":[145],"methods.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
