{"id":"https://openalex.org/W4293811421","doi":"https://doi.org/10.1109/tsp.2022.3203225","title":"Distributionally Robust State Estimation for Nonlinear Systems","display_name":"Distributionally Robust State Estimation for Nonlinear Systems","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4293811421","doi":"https://doi.org/10.1109/tsp.2022.3203225"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3203225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3203225","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","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/A5070552557","display_name":"Shixiong Wang","orcid":"https://orcid.org/0000-0001-7928-6918"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Shixiong Wang","raw_affiliation_strings":["Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-7928-6918","affiliations":[{"raw_affiliation_string":"Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070552557"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":2.6243,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91140503,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"70","issue":null,"first_page":"4408","last_page":"4423"},"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":0.9955000281333923,"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":0.9955000281333923,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9872999787330627,"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/T11186","display_name":"Hydrology and Drought Analysis","score":0.9589999914169312,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6471425294876099},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6059418320655823},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5754102468490601},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.5625227093696594},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.5605146288871765},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5548353791236877},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.5354964733123779},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.4579244554042816},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.44827744364738464},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4380953311920166},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4156540036201477},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4152211546897888},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.260114461183548}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6471425294876099},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6059418320655823},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5754102468490601},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.5625227093696594},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.5605146288871765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5548353791236877},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.5354964733123779},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4579244554042816},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.44827744364738464},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4380953311920166},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4156540036201477},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4152211546897888},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.260114461183548},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3203225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3203225","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":75,"referenced_works":["https://openalex.org/W1024801928","https://openalex.org/W1484551447","https://openalex.org/W1501586228","https://openalex.org/W1503398984","https://openalex.org/W1572031236","https://openalex.org/W1585160083","https://openalex.org/W1590693676","https://openalex.org/W1686266550","https://openalex.org/W1749494163","https://openalex.org/W1954573324","https://openalex.org/W1965555277","https://openalex.org/W1968355947","https://openalex.org/W1988520084","https://openalex.org/W1995875735","https://openalex.org/W2000721204","https://openalex.org/W2019038153","https://openalex.org/W2040196349","https://openalex.org/W2051234657","https://openalex.org/W2052958516","https://openalex.org/W2054091988","https://openalex.org/W2057798714","https://openalex.org/W2058568645","https://openalex.org/W2065313971","https://openalex.org/W2099111195","https://openalex.org/W2111787305","https://openalex.org/W2123748412","https://openalex.org/W2125417745","https://openalex.org/W2140242774","https://openalex.org/W2143737806","https://openalex.org/W2145834063","https://openalex.org/W2151084831","https://openalex.org/W2156707583","https://openalex.org/W2160337655","https://openalex.org/W2162719021","https://openalex.org/W2162733643","https://openalex.org/W2167229292","https://openalex.org/W2295695367","https://openalex.org/W2427096884","https://openalex.org/W2490662969","https://openalex.org/W2502922730","https://openalex.org/W2515453889","https://openalex.org/W2570372101","https://openalex.org/W2582119505","https://openalex.org/W2588781374","https://openalex.org/W2735102987","https://openalex.org/W2790374560","https://openalex.org/W2806458225","https://openalex.org/W2810968776","https://openalex.org/W2908120081","https://openalex.org/W2912753047","https://openalex.org/W2944290312","https://openalex.org/W2963450292","https://openalex.org/W2964110122","https://openalex.org/W2969738732","https://openalex.org/W3106340677","https://openalex.org/W3110740850","https://openalex.org/W3111719083","https://openalex.org/W3113256900","https://openalex.org/W3120253624","https://openalex.org/W3123857276","https://openalex.org/W3129335301","https://openalex.org/W3132712038","https://openalex.org/W3205227205","https://openalex.org/W3210029897","https://openalex.org/W4206324394","https://openalex.org/W4206328009","https://openalex.org/W4213194861","https://openalex.org/W4213251304","https://openalex.org/W4250589301","https://openalex.org/W4285105952","https://openalex.org/W4300580367","https://openalex.org/W6676780147","https://openalex.org/W6741832134","https://openalex.org/W6745312988","https://openalex.org/W6922278327"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2015530857","https://openalex.org/W2614538623","https://openalex.org/W2760778703","https://openalex.org/W4361200497","https://openalex.org/W2327008140","https://openalex.org/W4389041422","https://openalex.org/W2742795413"],"abstract_inverted_index":{"Uncertainties":[0],"unavoidably":[1],"exist":[2],"in":[3,64,153,188,238],"modeling":[4,41,91],"for":[5,86,219],"nonlinear":[6,87,221],"systems:":[7],"state":[8,27,69,98,104,109,133,197],"equation,":[9,11],"measurement":[10,222,228,234],"and/or":[12,111],"noises":[13],"statistics":[14],"might":[15],"be":[16,45],"uncertain.":[17],"Such":[18],"model":[19],"mismatches":[20],"render":[21],"the":[22,53,101,120,128,189,208,239],"performance":[23],"of":[24,131,145],"nominally":[25],"optimal":[26],"estimators":[28],"being":[29],"deteriorated":[30],"or":[31],"even":[32],"unsatisfactory.":[33],"Therefore,":[34],"robust":[35,60,82,187,210,241],"filters":[36,180],"that":[37,177,191,207],"are":[38,124,151,185],"insensitive":[39],"to":[40,44,50,90,106,126],"uncertainties":[42,54,63],"have":[43],"designed.":[46],"The":[47,138],"challenge":[48],"is":[49,141],"quantitatively":[51],"describe":[52],"and":[55,71,147,172,199,226],"then":[56],"design":[57],"accordingly":[58],"efficient":[59],"filters.":[61],"Since":[62],"nominal":[65,102,121,157],"models":[66],"make":[67],"prior":[68,97,103,108,132,196],"distributions":[70,73,99,118,150,158,198],"likelihood":[72,117,122,202,216],"uncertain":[74],"as":[75,167],"well,":[76],"this":[77],"article":[78],"proposes":[79],"a":[80,215],"distributionally":[81,186,209,240],"particle":[83,211,242],"filtering":[84,212,243],"framework":[85,213],"systems":[88],"subject":[89],"uncertainties.":[92],"Specifically,":[93],"we":[94,205,232],"use":[95,193],"worst-case":[96,116,129],"(near":[100,119],"distributions)":[105,123],"generate":[107],"particles":[110,134],"determine":[112],"their":[113],"weights.":[114],"Likewise,":[115],"used":[125],"evaluate":[127],"likelihoods":[130],"at":[135,156],"given":[136],"measurements.":[137],"\u201cworst-case\u201d":[139],"scenario":[140],"quantified":[142],"by":[143,162],"entropy":[144,149,195,201],"distributions,":[146],"maximum":[148,194,200],"found":[152],"balls":[154],"centered":[155],"with":[159,224],"radii":[160],"defined":[161],"statistical":[163],"similarity":[164],"measures":[165],"such":[166],"moments-based":[168],"similarity,":[169],"Wasserstein":[170],"distance,":[171],"Kullback-Leibler":[173],"divergence.":[174],"We":[175],"prove":[176],"Gaussian":[178],"approximation":[179],"(e.g.,":[181],"unscented/cubature/ensemble":[182],"Kalman":[183],"filter)":[184],"sense":[190],"they":[192],"distributions.":[203],"Moreover,":[204],"show":[206],"provides":[214],"evaluation":[217],"method":[218],"general":[220],"equation":[223],"non-additive":[225],"non-multiplicative":[227],"noises.":[229],"At":[230],"last,":[231],"discuss":[233],"outlier":[235],"treatment":[236],"strategies":[237],"framework.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
