{"id":"https://openalex.org/W4417131186","doi":"https://doi.org/10.1109/tie.2025.3632480","title":"Gaussian Classifier-Based Robust Mixture Distribution Kalman Filter for GNSS/INS Integrated System on Land Vehicle","display_name":"Gaussian Classifier-Based Robust Mixture Distribution Kalman Filter for GNSS/INS Integrated System on Land Vehicle","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W4417131186","doi":"https://doi.org/10.1109/tie.2025.3632480"},"language":null,"primary_location":{"id":"doi:10.1109/tie.2025.3632480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2025.3632480","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial Electronics","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/A5080896563","display_name":"Zengke Li","orcid":"https://orcid.org/0000-0001-6590-3591"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengke Li","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6590-3591","affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079653906","display_name":"Zhaobing Chen","orcid":"https://orcid.org/0000-0001-7591-2360"},"institutions":[{"id":"https://openalex.org/I2799888197","display_name":"Boiron (France)","ror":"https://ror.org/049f4wb20","country_code":"FR","type":"company","lineage":["https://openalex.org/I2799888197"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Zhaobing Chen","raw_affiliation_strings":["Hangzhou Yunjian Zhirong Information Technology Co. Ltd., Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7591-2360","affiliations":[{"raw_affiliation_string":"Hangzhou Yunjian Zhirong Information Technology Co. Ltd., Hangzhou, China","institution_ids":["https://openalex.org/I2799888197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042999384","display_name":"Zhenqiang Tao","orcid":"https://orcid.org/0009-0002-3592-8354"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenqiang Tao","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-3592-8354","affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076620228","display_name":"Cheng Pan","orcid":"https://orcid.org/0000-0002-3948-9558"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Pan","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3948-9558","affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048931970","display_name":"Zhisheng Zhao","orcid":"https://orcid.org/0000-0001-9438-257X"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhisheng Zhao","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9438-257X","affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2331,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8653423,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"73","issue":"4","first_page":"6199","last_page":"6210"},"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":0.620199978351593,"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":0.620199978351593,"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/T11325","display_name":"Inertial Sensor and Navigation","score":0.20720000565052032,"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/T10655","display_name":"GNSS positioning and interference","score":0.052799999713897705,"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/robustness","display_name":"Robustness (evolution)","score":0.7993999719619751},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.765500009059906},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7092999815940857},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5329999923706055},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4593999981880188},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.4481000006198883},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.43050000071525574},{"id":"https://openalex.org/keywords/invariant-extended-kalman-filter","display_name":"Invariant extended Kalman filter","score":0.4259999990463257},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4178999960422516}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7993999719619751},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.765500009059906},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7092999815940857},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5529999732971191},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5329999923706055},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5048999786376953},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4593999981880188},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.4481000006198883},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.43050000071525574},{"id":"https://openalex.org/C8639503","wikidata":"https://www.wikidata.org/wiki/Q6059511","display_name":"Invariant extended Kalman filter","level":4,"score":0.4259999990463257},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4178999960422516},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3910999894142151},{"id":"https://openalex.org/C150679823","wikidata":"https://www.wikidata.org/wiki/Q5436946","display_name":"Fast Kalman filter","level":4,"score":0.3772999942302704},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3452000021934509},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.33480000495910645},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3019999861717224},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C2777891301","wikidata":"https://www.wikidata.org/wiki/Q3475123","display_name":"Navigation system","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.27070000767707825},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.25780001282691956},{"id":"https://openalex.org/C39425265","wikidata":"https://www.wikidata.org/wiki/Q7098944","display_name":"Optimal estimation","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C162500139","wikidata":"https://www.wikidata.org/wiki/Q2835887","display_name":"Estimation of distribution algorithm","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C40343088","wikidata":"https://www.wikidata.org/wiki/Q3059012","display_name":"Recursive Bayesian estimation","level":3,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tie.2025.3632480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2025.3632480","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1371195803","display_name":null,"funder_award_id":"42274020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4716527777","display_name":null,"funder_award_id":"2025QN1108","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1994364263","https://openalex.org/W2027881735","https://openalex.org/W2035300031","https://openalex.org/W2575097171","https://openalex.org/W2724913661","https://openalex.org/W2806131213","https://openalex.org/W2944846513","https://openalex.org/W2963134661","https://openalex.org/W3006216141","https://openalex.org/W3121115497","https://openalex.org/W3136138523","https://openalex.org/W3190272655","https://openalex.org/W3197302491","https://openalex.org/W4213300369","https://openalex.org/W4226177187","https://openalex.org/W4249736682","https://openalex.org/W4288059539","https://openalex.org/W4312336651","https://openalex.org/W4313593929","https://openalex.org/W4319265311","https://openalex.org/W4381886288","https://openalex.org/W4383226501","https://openalex.org/W4385063002","https://openalex.org/W4387642995","https://openalex.org/W4388571960","https://openalex.org/W4389396129","https://openalex.org/W4391528167","https://openalex.org/W4392349866","https://openalex.org/W4399704407","https://openalex.org/W4400065591","https://openalex.org/W4401415790","https://openalex.org/W4402389311"],"related_works":[],"abstract_inverted_index":{"Global":[0],"navigation":[1,82],"satellite":[2],"system":[3,83],"(GNSS)":[4],"signals":[5],"will":[6,13],"produce":[7],"outliers":[8],"when":[9],"interfered":[10],"with,":[11],"which":[12,173],"result":[14],"in":[15,223],"the":[16,47,60,77,80,92,101,105,110,117,121,127,130,134,165,171,177,182,193,198,215,220],"heavy-tailed":[17,208],"characteristics":[18],"of":[19,79,170,181,207,219],"measurement":[20],"noise.":[21],"The":[22,38,114,184],"traditional":[23],"Kalman":[24,71,148],"filter":[25,72,149],"based":[26],"on":[27],"Gaussian":[28,52,90],"distribution":[29,42,70],"is":[30,73,98,151,174],"no":[31],"longer":[32],"suitable":[33],"for":[34,204],"this":[35],"complex":[36],"scene.":[37],"Gaussian-student\u2019s":[39,66,143],"t":[40,67,144],"mixture":[41,61,69,145],"can":[43],"be":[44],"adapted":[45],"to":[46,75,176],"state":[48],"estimation":[49,103,160],"where":[50],"both":[51],"and":[53,109,120,133,168,179,201,217],"non-Gaussian":[54],"assumptions":[55],"are":[56,137],"present":[57],"by":[58],"adjusting":[59],"parameters.":[62],"A":[63],"novel":[64],"multidimensional":[65,142],"robust":[68,147],"proposed":[74,194,221],"improve":[76],"robustness":[78,102,200],"GNSS/inertial":[81],"(INS)":[84],"integrated":[85,225],"system.":[86,226],"By":[87],"introducing":[88],"a":[89,141],"classifier,":[91],"original":[93],"variational":[94],"Bayesian":[95],"optimization":[96,122],"process":[97],"divided":[99],"into":[100],"part,":[104,108],"prior":[106,118],"weight":[107],"classification":[111],"probability":[112],"part.":[113],"relation":[115,128],"between":[116,129],"parameters":[119,132],"results,":[123],"as":[124,126],"well":[125],"estimated":[131],"iterative":[135],"process,":[136],"revealed.":[138],"In":[139],"addition,":[140],"distribution-based":[146],"(SIG-MGSTM)":[150],"proposed.":[152],"This":[153],"method":[154],"avoids":[155],"multiple":[156],"iterations":[157],"while":[158],"ensuring":[159],"accuracy,":[161],"thus":[162],"significantly":[163],"reducing":[164],"computational":[166],"load":[167],"complexity":[169],"algorithm,":[172],"conducive":[175],"expansion":[178],"application":[180],"algorithm.":[183],"simulation":[185],"results":[186],"show":[187],"that":[188],"compared":[189],"with":[190],"other":[191],"schemes,":[192],"SIG-MGSTM":[195],"algorithm":[196,222],"has":[197],"best":[199],"real-time":[202],"performance":[203],"different":[205],"levels":[206],"noise":[209],"scenes.":[210],"Outdoor":[211],"vehicle":[212],"experiments":[213],"verify":[214],"feasibility":[216],"practicability":[218],"GNSS/INS":[224]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-12-08T00:00:00"}