{"id":"https://openalex.org/W4314946942","doi":"https://doi.org/10.1109/cdc51059.2022.9992671","title":"On the Accuracy of the One-step UKF and the Two-step UKF","display_name":"On the Accuracy of the One-step UKF and the Two-step UKF","publication_year":2022,"publication_date":"2022-12-06","ids":{"openalex":"https://openalex.org/W4314946942","doi":"https://doi.org/10.1109/cdc51059.2022.9992671"},"language":"en","primary_location":{"id":"doi:10.1109/cdc51059.2022.9992671","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cdc51059.2022.9992671","pdf_url":null,"source":{"id":"https://openalex.org/S4363607710","display_name":"2022 IEEE 61st Conference on Decision and Control (CDC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 61st Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5036467105","display_name":"Ankit Goel","orcid":"https://orcid.org/0000-0002-4146-6275"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ankit Goel","raw_affiliation_strings":["University of Maryland,Department of Mechanical Engineering,Baltimore County,MD,21250"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland,Department of Mechanical Engineering,Baltimore County,MD,21250","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009770702","display_name":"Dennis S. Bernstein","orcid":"https://orcid.org/0000-0003-0399-3039"},"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":"Dennis S. Bernstein","raw_affiliation_strings":["University of Michigan,Department of Aerospace Engineering,Ann Arbor,MI,48109"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan,Department of Aerospace Engineering,Ann Arbor,MI,48109","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3374,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58089699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5375","last_page":"5380"},"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":0.9986000061035156,"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":0.9986000061035156,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.9086196422576904},{"id":"https://openalex.org/keywords/unscented-transform","display_name":"Unscented transform","score":0.679628849029541},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6570814847946167},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.6274325847625732},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5502890348434448},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.49324625730514526},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.48382821679115295},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4449806809425354},{"id":"https://openalex.org/keywords/invariant-extended-kalman-filter","display_name":"Invariant extended Kalman filter","score":0.4318317174911499},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.43160921335220337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19602343440055847},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.11216521263122559}],"concepts":[{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.9086196422576904},{"id":"https://openalex.org/C139399703","wikidata":"https://www.wikidata.org/wiki/Q7897426","display_name":"Unscented transform","level":5,"score":0.679628849029541},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6570814847946167},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.6274325847625732},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5502890348434448},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.49324625730514526},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.48382821679115295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4449806809425354},{"id":"https://openalex.org/C8639503","wikidata":"https://www.wikidata.org/wiki/Q6059511","display_name":"Invariant extended Kalman filter","level":4,"score":0.4318317174911499},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.43160921335220337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19602343440055847},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.11216521263122559},{"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/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc51059.2022.9992671","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cdc51059.2022.9992671","pdf_url":null,"source":{"id":"https://openalex.org/S4363607710","display_name":"2022 IEEE 61st Conference on Decision and Control (CDC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 61st Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1749494163","https://openalex.org/W2020934227","https://openalex.org/W2044474419","https://openalex.org/W2057539615","https://openalex.org/W2073389244","https://openalex.org/W2121754060","https://openalex.org/W2126423185","https://openalex.org/W2137183867","https://openalex.org/W2179584279","https://openalex.org/W2783323062","https://openalex.org/W2790374560","https://openalex.org/W4232464081"],"related_works":["https://openalex.org/W2053335193","https://openalex.org/W2350305363","https://openalex.org/W4206024512","https://openalex.org/W3086876622","https://openalex.org/W4206622494","https://openalex.org/W2917624112","https://openalex.org/W2370718670","https://openalex.org/W4287243885","https://openalex.org/W3080167830","https://openalex.org/W2188632562"],"abstract_inverted_index":{"The":[0],"most":[1],"accurate":[2],"version":[3],"of":[4,13,43,59,93],"the":[5,11,26,40,44,51,74,85,91,94],"unscented":[6],"Kalman":[7,53,76],"filter":[8,77],"(UKF)":[9],"involves":[10],"construction":[12],"two":[14],"ensembles.":[15],"To":[16],"reduce":[17],"computational":[18],"cost,":[19],"however,":[20,35],"UKF":[21,46,71,88,96],"is":[22],"often":[23],"implemented":[24],"without":[25],"second":[27],"ensemble.":[28],"This":[29,61],"simplification":[30],"comes":[31],"at":[32],"a":[33,68],"price,":[34],"since,":[36],"for":[37,78],"linear":[38,79,101],"systems,":[39],"one-step":[41,70,87],"variation":[42],"two-step":[45,95],"does":[47],"not":[48],"specialize":[49],"to":[50],"classical":[52,75],"filter,":[54],"with":[55,100],"an":[56],"associated":[57],"loss":[58],"accuracy.":[60],"paper":[62],"remedies":[63],"this":[64],"drawback":[65],"by":[66],"developing":[67],"modified":[69,86],"that":[72,84],"recovers":[73,90],"systems.":[80],"Numerical":[81],"examples":[82],"show":[83],"also":[89],"accuracy":[92],"in":[97],"nonlinear":[98],"systems":[99],"outputs.":[102]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
