{"id":"https://openalex.org/W4308121896","doi":"https://doi.org/10.3390/rs14215477","title":"Reweighted Robust Particle Filtering Approach for Target Tracking in Automotive Radar Application","display_name":"Reweighted Robust Particle Filtering Approach for Target Tracking in Automotive Radar Application","publication_year":2022,"publication_date":"2022-10-31","ids":{"openalex":"https://openalex.org/W4308121896","doi":"https://doi.org/10.3390/rs14215477"},"language":"en","primary_location":{"id":"doi:10.3390/rs14215477","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215477","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5477/pdf?version=1667217464","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/21/5477/pdf?version=1667217464","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076758349","display_name":"Qisong Wu","orcid":"https://orcid.org/0000-0002-2114-7672"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"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":true,"raw_author_name":"Qisong Wu","raw_affiliation_strings":["Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China","Purple Mountain Laboratories, Nanjing 211111, China"],"raw_orcid":"https://orcid.org/0000-0002-2114-7672","affiliations":[{"raw_affiliation_string":"Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Nanjing 211111, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104668357","display_name":"Lingjie Chen","orcid":"https://orcid.org/0009-0003-5567-829X"},"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":"Lingjie Chen","raw_affiliation_strings":["Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385632","display_name":"Yanping Li","orcid":"https://orcid.org/0000-0002-0074-7695"},"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":"Yanping Li","raw_affiliation_strings":["Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100729843","display_name":"Zijun Wang","orcid":"https://orcid.org/0009-0002-1261-2760"},"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":"Zijun Wang","raw_affiliation_strings":["Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023123451","display_name":"Shuai Yao","orcid":"https://orcid.org/0000-0001-6462-4670"},"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":"Shuai Yao","raw_affiliation_strings":["Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100348617","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-6294-6761"},"institutions":[{"id":"https://openalex.org/I4210140031","display_name":"Science and Technology on Surface Physics and Chemistry Laboratory","ror":"https://ror.org/0543q7s13","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210140031"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["Science and Technology on Near-Surface Detection Laboratory, Wuxi 214035, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Near-Surface Detection Laboratory, Wuxi 214035, China","institution_ids":["https://openalex.org/I4210140031"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076758349"],"corresponding_institution_ids":["https://openalex.org/I4210155350","https://openalex.org/I76569877"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.6551,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74223784,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"14","issue":"21","first_page":"5477","last_page":"5477"},"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9865000247955322,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.8099737167358398},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6839297413825989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6545360088348389},{"id":"https://openalex.org/keywords/state-vector","display_name":"State vector","score":0.5916116833686829},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5185235738754272},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5038706660270691},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.4793334901332855},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.46062415838241577},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4592745900154114},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4135201871395111},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.398947149515152},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36547040939331055},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14037659764289856},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07772111892700195}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.8099737167358398},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6839297413825989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6545360088348389},{"id":"https://openalex.org/C2777798563","wikidata":"https://www.wikidata.org/wiki/Q7603916","display_name":"State vector","level":2,"score":0.5916116833686829},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5185235738754272},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5038706660270691},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.4793334901332855},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.46062415838241577},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4592745900154114},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4135201871395111},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.398947149515152},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36547040939331055},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14037659764289856},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07772111892700195},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14215477","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215477","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5477/pdf?version=1667217464","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:95f5d32b6f2243d9bb86ee193b977434","is_oa":true,"landing_page_url":"https://doaj.org/article/95f5d32b6f2243d9bb86ee193b977434","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 21, p 5477 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/21/5477/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14215477","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 21; Pages: 5477","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14215477","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215477","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5477/pdf?version=1667217464","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2749008688","display_name":null,"funder_award_id":"2022JCJQLB03305","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3428498163","display_name":null,"funder_award_id":"6142414200505","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8526846093","display_name":null,"funder_award_id":"JCKY2019110C143","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G997914651","display_name":null,"funder_award_id":"91938203","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4308121896.pdf","grobid_xml":"https://content.openalex.org/works/W4308121896.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1976974773","https://openalex.org/W2018890348","https://openalex.org/W2042688433","https://openalex.org/W2049567111","https://openalex.org/W2104130465","https://openalex.org/W2105934661","https://openalex.org/W2131458171","https://openalex.org/W2148163819","https://openalex.org/W2160337655","https://openalex.org/W2163152452","https://openalex.org/W2166787100","https://openalex.org/W2263559961","https://openalex.org/W2395026957","https://openalex.org/W2402392024","https://openalex.org/W2531569435","https://openalex.org/W2551758879","https://openalex.org/W2737188128","https://openalex.org/W2742749798","https://openalex.org/W2897396640","https://openalex.org/W2969611331","https://openalex.org/W3110918660","https://openalex.org/W3120148904","https://openalex.org/W3135850304","https://openalex.org/W3155840365","https://openalex.org/W3168070935","https://openalex.org/W6680548674","https://openalex.org/W6766876578","https://openalex.org/W6791343519"],"related_works":["https://openalex.org/W1989212443","https://openalex.org/W2103644279","https://openalex.org/W4302986566","https://openalex.org/W1968585197","https://openalex.org/W2135362996","https://openalex.org/W2150578674","https://openalex.org/W877199042","https://openalex.org/W2122155275","https://openalex.org/W4247544095","https://openalex.org/W2535707089"],"abstract_inverted_index":{"In":[0],"view":[1],"of":[2,5,38,80,97,109],"the":[3,36,42,59,69,84,94,98,107,110],"decline":[4],"filtering":[6],"accuracy":[7],"caused":[8],"by":[9],"measured":[10,60],"outliers":[11],"in":[12,29,41,83],"target":[13],"tracking":[14],"application,":[15],"a":[16,49,54],"novel":[17],"reweighted":[18],"robust":[19,115],"particle":[20,70],"filter":[21,71],"is":[22,73,91],"proposed":[23,99,111],"to":[24,57,75],"acquire":[25],"accurate":[26,65],"state":[27,66,81],"estimates":[28,82],"an":[30],"automotive":[31],"radar":[32],"system.":[33],"To":[34],"infer":[35],"importance":[37],"each":[39],"entry":[40],"multidimensional":[43],"contaminated":[44],"measurement":[45],"vector,":[46,51],"we":[47],"employ":[48],"weight":[50],"which":[52],"follows":[53],"Gamma":[55],"distribution,":[56],"model":[58],"noise":[61],"and":[62,103],"carry":[63],"out":[64],"estimates.":[67],"Additionally,":[68],"method":[72],"employed":[74],"perform":[76],"approximate":[77],"posterior":[78],"inference":[79],"nonlinear":[85],"model.":[86],"The":[87],"Cramer\u2013Rao":[88],"lower":[89],"bound":[90],"provided":[92],"for":[93],"performance":[95],"evaluation":[96],"method.":[100],"Both":[101],"simulation":[102],"experimental":[104],"results":[105],"demonstrate":[106],"superiorities":[108],"algorithm":[112],"over":[113],"other":[114],"solutions.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-07T14:30:12.667765","created_date":"2022-11-08T00:00:00"}