{"id":"https://openalex.org/W2981021779","doi":"https://doi.org/10.23919/acc45564.2020.9147485","title":"Fitting a Kalman Smoother to Data","display_name":"Fitting a Kalman Smoother to Data","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W2981021779","doi":"https://doi.org/10.23919/acc45564.2020.9147485","mag":"2981021779"},"language":"en","primary_location":{"id":"doi:10.23919/acc45564.2020.9147485","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc45564.2020.9147485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 American Control Conference (ACC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.08615","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023055112","display_name":"Shane Barratt","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shane T. Barratt","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA","Department of Electrical Engineering, Stanford University, Stanford, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA#TAB#","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011176205","display_name":"Stephen Boyd","orcid":"https://orcid.org/0000-0001-8353-6000"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen P. Boyd","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA","Department of Electrical Engineering, Stanford University, Stanford, CA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA#TAB#","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":0.1354,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52274338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1526","last_page":"1531"},"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":0.996999979019165,"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":0.996999979019165,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9760000109672546,"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":0.8157682418823242},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.695859432220459},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6258495450019836},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5613982081413269},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.5073475241661072},{"id":"https://openalex.org/keywords/fast-kalman-filter","display_name":"Fast Kalman filter","score":0.5022788047790527},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.459451287984848},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4254749119281769},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4209754467010498},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41844603419303894},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.3112295866012573},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26998579502105713},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2415996491909027},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1552368402481079},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1114683449268341}],"concepts":[{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.8157682418823242},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.695859432220459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6258495450019836},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5613982081413269},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.5073475241661072},{"id":"https://openalex.org/C150679823","wikidata":"https://www.wikidata.org/wiki/Q5436946","display_name":"Fast Kalman filter","level":4,"score":0.5022788047790527},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.459451287984848},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4254749119281769},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4209754467010498},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41844603419303894},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.3112295866012573},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26998579502105713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2415996491909027},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1552368402481079},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1114683449268341},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.23919/acc45564.2020.9147485","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc45564.2020.9147485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 American Control Conference (ACC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1910.08615","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.08615","pdf_url":"https://arxiv.org/pdf/1910.08615","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2981021779","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/1910.08615.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1910.08615","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.08615","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.08615","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.08615","pdf_url":"https://arxiv.org/pdf/1910.08615","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.8299999833106995,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2499887605","display_name":null,"funder_award_id":"DGE-1656518","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G320138474","display_name":null,"funder_award_id":"-1656518","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5267932457","display_name":"Graduate Research Fellowship Program (GRFP)","funder_award_id":"1656518","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2981021779.pdf","grobid_xml":"https://content.openalex.org/works/W2981021779.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W169414593","https://openalex.org/W304861154","https://openalex.org/W823688676","https://openalex.org/W1963718895","https://openalex.org/W1972637587","https://openalex.org/W2003372231","https://openalex.org/W2015263936","https://openalex.org/W2019569173","https://openalex.org/W2030161963","https://openalex.org/W2051917325","https://openalex.org/W2102261079","https://openalex.org/W2105934661","https://openalex.org/W2146292423","https://openalex.org/W2296319761","https://openalex.org/W2543381247","https://openalex.org/W2913535645","https://openalex.org/W2939592218","https://openalex.org/W2962771180","https://openalex.org/W3005347330","https://openalex.org/W3022251767","https://openalex.org/W3141595720","https://openalex.org/W4211092921","https://openalex.org/W4232936225","https://openalex.org/W4244393449","https://openalex.org/W4250589301","https://openalex.org/W4250772482","https://openalex.org/W6623108078","https://openalex.org/W6773842061"],"related_works":["https://openalex.org/W2979647272","https://openalex.org/W154211054","https://openalex.org/W2905886676","https://openalex.org/W2169329579","https://openalex.org/W2057257803","https://openalex.org/W1574649625","https://openalex.org/W2887454604","https://openalex.org/W1983510162","https://openalex.org/W2267569236","https://openalex.org/W190762733","https://openalex.org/W2795497518","https://openalex.org/W2373945327","https://openalex.org/W2356534457","https://openalex.org/W3019619473","https://openalex.org/W2147929628","https://openalex.org/W1556832804","https://openalex.org/W2896186333","https://openalex.org/W3180146037","https://openalex.org/W1547865965","https://openalex.org/W2112959694"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"the":[3,7,17,44,55,78,87,99,102,105,109,116,119,127,137,143],"problem":[4,20,29],"of":[5,101,104,118],"fitting":[6],"parameters":[8,53,89,117],"in":[9,54],"a":[10,25,69,91,152],"Kalman":[11,18,45,56,70,120],"smoother":[12,46,57,71],"to":[13,51,58,95,115,125,131],"data.":[14],"We":[15,41,67,135],"formulate":[16],"smoothing":[19],"with":[21,113],"missing":[22],"measurements":[23,112],"as":[24,146,148],"constrained":[26],"least":[27],"squares":[28],"and":[30],"provide":[31],"an":[32],"efficient":[33],"solution":[34],"method":[35,97,138],"based":[36,76],"on":[37,63,77,108,139],"sparse":[38],"linear":[39],"algebra.":[40],"then":[42],"introduce":[43],"tuning":[47],"problem,":[48],"which":[49,74],"seeks":[50],"adjust":[52],"achieve":[59],"low":[60],"prediction":[61,106],"error":[62,107],"held":[64,110],"out":[65,111],"measurements.":[66],"derive":[68],"auto-tuning":[72],"algorithm,":[73],"is":[75,98],"proximal":[79],"gradient":[80,103,128],"method,":[81],"that":[82],"finds":[83],"good,":[84],"if":[85],"not":[86],"best,":[88],"for":[90],"given":[92],"dataset.":[93],"Central":[94],"our":[96],"computation":[100],"respect":[114],"smoother;":[121],"we":[122],"describe":[123],"how":[124],"compute":[126],"at":[129],"little":[130],"no":[132],"additional":[133],"cost.":[134],"demonstrate":[136],"population":[140],"migration":[141],"within":[142],"United":[144],"States":[145],"well":[147],"data":[149],"collected":[150],"from":[151],"smartphone's":[153],"IMU+GPS":[154],"system":[155],"while":[156],"driving.":[157]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
