{"id":"https://openalex.org/W4380450972","doi":"https://doi.org/10.1109/lsp.2023.3285118","title":"Outlier-Robust Iterative Extended Kalman Filtering","display_name":"Outlier-Robust Iterative Extended Kalman Filtering","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4380450972","doi":"https://doi.org/10.1109/lsp.2023.3285118"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2023.3285118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3285118","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5048234832","display_name":"Yangtianze Tao","orcid":"https://orcid.org/0000-0002-3775-6712"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yangtianze Tao","raw_affiliation_strings":["Department of Mathematical Sciences, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019752361","display_name":"Stephen S.\u2010T. Yau","orcid":"https://orcid.org/0000-0001-7634-7981"},"institutions":[{"id":"https://openalex.org/I4403928416","display_name":"Beijing Institute of Mathematical Sciences and Applications","ror":"https://ror.org/05t6hvr95","country_code":null,"type":"education","lineage":["https://openalex.org/I4403928416","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Stephen Shing-Toung Yau","raw_affiliation_strings":["Department of Mathematical Sciences, Tsinghua University, Beijing, China","Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, Huairou district, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, Huairou district, Beijing, China","institution_ids":["https://openalex.org/I4403928416"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048234832"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":8.1945,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.98182092,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"30","issue":null,"first_page":"743","last_page":"747"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11236","display_name":"Control Systems and Identification","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/outlier","display_name":"Outlier","score":0.7805043458938599},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.7372630834579468},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6690073609352112},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.5887752771377563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5296406745910645},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5259480476379395},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5108199119567871},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4879166781902313},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.47479337453842163},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.47159895300865173},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.43816718459129333},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.43616020679473877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40852034091949463},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3793480694293976},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37556958198547363},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1437687873840332},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06697601079940796}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7805043458938599},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7372630834579468},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6690073609352112},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.5887752771377563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5296406745910645},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5259480476379395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5108199119567871},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4879166781902313},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.47479337453842163},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.47159895300865173},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.43816718459129333},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.43616020679473877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40852034091949463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3793480694293976},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37556958198547363},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1437687873840332},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06697601079940796},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2023.3285118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3285118","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G938812237","display_name":null,"funder_award_id":"11961141005","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":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1995087757","https://openalex.org/W2016456873","https://openalex.org/W2020934227","https://openalex.org/W2028496557","https://openalex.org/W2047448918","https://openalex.org/W2098613108","https://openalex.org/W2105934661","https://openalex.org/W2122512809","https://openalex.org/W2135160607","https://openalex.org/W2139182243","https://openalex.org/W2166713810","https://openalex.org/W2294322297","https://openalex.org/W2553413742","https://openalex.org/W2575097171","https://openalex.org/W2790374560","https://openalex.org/W2963134661","https://openalex.org/W2997297215","https://openalex.org/W3112682751","https://openalex.org/W4226120776","https://openalex.org/W4230367971","https://openalex.org/W4247915326","https://openalex.org/W4249736682","https://openalex.org/W4253886630","https://openalex.org/W4307723610","https://openalex.org/W4312520746"],"related_works":["https://openalex.org/W2089114113","https://openalex.org/W2389555968","https://openalex.org/W2352634297","https://openalex.org/W80107739","https://openalex.org/W2020144404","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,72],"develop":[4],"OR-IEKF":[5,43],"which":[6,45],"is":[7],"a":[8,85],"novel":[9],"outlier-robust":[10],"iterative":[11],"extended":[12],"Kalman":[13],"filtering":[14],"(IEKF)":[15],"framework":[16],"based":[17],"on":[18],"nonlinear":[19,69,86],"regression":[20,70],"formulation":[21],"of":[22,78],"update":[23,28],"step.":[24],"A":[25],"new":[26,80],"Kalman-type":[27],"step":[29],"with":[30],"reweighted":[31,35],"prediction":[32],"covariance":[33,38],"and":[34],"observation":[36],"noise":[37],"are":[39,82],"produced":[40],"under":[41],"the":[42,49],"framework,":[44],"could":[46],"cut":[47],"off":[48],"large":[50],"outliers":[51],"in":[52,84],"observations":[53],"causing":[54],"by":[55],"unknown":[56],"outlier":[57],"noises.":[58],"By":[59],"using":[60],"various":[61],"robust":[62],"cost":[63],"functions":[64],"to":[65],"solve":[66],"such":[67],"special":[68],"problems,":[71],"derive":[73],"three":[74],"algorithms.":[75],"The":[76],"performances":[77],"these":[79],"filters":[81],"evaluated":[83],"system":[87],"simulation":[88],"study.":[89]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
