{"id":"https://openalex.org/W4399849857","doi":"https://doi.org/10.1109/tsp.2024.3417350","title":"EKFNet: Learning System Noise Covariance Parameters for Nonlinear Tracking","display_name":"EKFNet: Learning System Noise Covariance Parameters for Nonlinear Tracking","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399849857","doi":"https://doi.org/10.1109/tsp.2024.3417350"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2024.3417350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3417350","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/A5100342486","display_name":"Liang Xu","orcid":"https://orcid.org/0000-0003-1592-6175"},"institutions":[{"id":"https://openalex.org/I4210133016","display_name":"Motion Control (United States)","ror":"https://ror.org/03yjg6e54","country_code":"US","type":"company","lineage":["https://openalex.org/I4210133016"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Liang Xu","raw_affiliation_strings":["Motional Inc., Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Motional Inc., Boston, MA, USA","institution_ids":["https://openalex.org/I4210133016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003828818","display_name":"Ruixin Niu","orcid":"https://orcid.org/0000-0003-2511-9174"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruixin Niu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA, USA","institution_ids":["https://openalex.org/I184840846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100342486"],"corresponding_institution_ids":["https://openalex.org/I4210133016"],"apc_list":null,"apc_paid":null,"fwci":3.6857,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.93401197,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"72","issue":null,"first_page":"3139","last_page":"3152"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9957000017166138,"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"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9957000017166138,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9911999702453613,"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/T11236","display_name":"Control Systems and Identification","score":0.9883999824523926,"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/covariance","display_name":"Covariance","score":0.7019902467727661},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6242570877075195},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6051180958747864},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5502333045005798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.541465163230896},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.48060867190361023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42273151874542236},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36753517389297485},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.35042333602905273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33361518383026123},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33199307322502136},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25232595205307007},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.17567682266235352},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09360828995704651}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.7019902467727661},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6242570877075195},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6051180958747864},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5502333045005798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.541465163230896},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.48060867190361023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42273151874542236},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36753517389297485},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.35042333602905273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33361518383026123},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33199307322502136},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25232595205307007},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.17567682266235352},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09360828995704651},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2024.3417350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2024.3417350","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":[{"id":"https://openalex.org/G3721755989","display_name":null,"funder_award_id":"FA9550-22-1-0038","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"},{"id":"https://openalex.org/G8871577853","display_name":null,"funder_award_id":"FA9550-18-1-0362","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W169414593","https://openalex.org/W1198835323","https://openalex.org/W1522301498","https://openalex.org/W1531532259","https://openalex.org/W1581808154","https://openalex.org/W1633338931","https://openalex.org/W1758624203","https://openalex.org/W2062803420","https://openalex.org/W2081854562","https://openalex.org/W2106432970","https://openalex.org/W2107823032","https://openalex.org/W2115579991","https://openalex.org/W2123487311","https://openalex.org/W2140242774","https://openalex.org/W2150355110","https://openalex.org/W2171371585","https://openalex.org/W2523246573","https://openalex.org/W2962771180","https://openalex.org/W2963121817","https://openalex.org/W2963203809","https://openalex.org/W2963371290","https://openalex.org/W2998415999","https://openalex.org/W3022577489","https://openalex.org/W3046091798","https://openalex.org/W3096786645","https://openalex.org/W3114773556","https://openalex.org/W3155879556","https://openalex.org/W3160166964","https://openalex.org/W3160206926","https://openalex.org/W3183282730","https://openalex.org/W3196221851","https://openalex.org/W3206324264","https://openalex.org/W4239782249","https://openalex.org/W4249212943","https://openalex.org/W4293094098","https://openalex.org/W4310363087","https://openalex.org/W6631190155","https://openalex.org/W6631209646","https://openalex.org/W6677422266","https://openalex.org/W6712730493","https://openalex.org/W6727249380","https://openalex.org/W6734797129","https://openalex.org/W6753773310","https://openalex.org/W6790829752","https://openalex.org/W6889657716","https://openalex.org/W7015832921"],"related_works":["https://openalex.org/W2327107878","https://openalex.org/W1526760723","https://openalex.org/W2171117985","https://openalex.org/W2012356576","https://openalex.org/W2126659863","https://openalex.org/W3112120395","https://openalex.org/W4385670989","https://openalex.org/W2102487628","https://openalex.org/W2009680848","https://openalex.org/W2150465873"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"to":[3,9,90],"reduce":[4],"the":[5,26,53,61,64,73,77,80,83,87,96,113,116,122,131],"time":[6,50,92],"and":[7,29,94,150],"manpower":[8],"fine-tune":[10],"an":[11,35,147],"extended":[12],"Kalman":[13],"filter":[14],"(EKF),":[15],"we":[16],"propose":[17],"a":[18,151],"new":[19],"learning":[20],"framework,":[21],"EKFNet,":[22],"for":[23,34,85],"automatically":[24],"estimating":[25],"best":[27],"process":[28],"measurement":[30,39,117],"noise":[31,98],"covariance":[32],"parameters":[33],"EKF":[36,66],"from":[37],"real":[38,142],"data.":[40,134],"The":[41,55,101,135],"EKFNet":[42,59,81],"is":[43,60,139],"trained":[44],"end-to-end":[45],"by":[46],"using":[47,141],"backpropagation":[48],"through":[49],"(BPTT)":[51],"over":[52],"EKF.":[54,154],"forward":[56],"operation":[57,67],"of":[58],"same":[62],"as":[63,111],"normal":[65],"which":[68,145],"will":[69],"be":[70],"used":[71],"during":[72],"tracking":[74],"process.":[75],"During":[76],"offline":[78],"training,":[79],"uses":[82],"BPTT":[84],"passing":[86],"gradient":[88],"flow":[89],"each":[91],"step":[93],"optimizing":[95],"unknown":[97],"statistic":[99],"parameters.":[100],"proposed":[102,136],"method":[103,149],"can":[104],"choose":[105],"among":[106],"several":[107],"optimization":[108],"criteria,":[109],"such":[110],"maximizing":[112],"likelihood,":[114],"minimizing":[115,121],"residual":[118],"error,":[119],"or":[120,129],"posterior":[123],"state":[124],"estimation":[125],"error":[126],"either":[127],"with":[128],"without":[130],"ground":[132],"truth":[133],"method's":[137],"performance":[138],"demonstrated":[140],"GPS":[143],"data,":[144],"outperforms":[146],"existing":[148],"manually":[152],"tuned":[153]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
