{"id":"https://openalex.org/W4313639556","doi":"https://doi.org/10.1109/lra.2023.3234778","title":"A Simple Self-Supervised IMU Denoising Method for Inertial Aided Navigation","display_name":"A Simple Self-Supervised IMU Denoising Method for Inertial Aided Navigation","publication_year":2023,"publication_date":"2023-01-06","ids":{"openalex":"https://openalex.org/W4313639556","doi":"https://doi.org/10.1109/lra.2023.3234778"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2023.3234778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3234778","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation 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/A5016673975","display_name":"Kaiwen Yuan","orcid":"https://orcid.org/0000-0003-4386-5373"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kaiwen Yuan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada"],"raw_orcid":"https://orcid.org/0000-0003-4386-5373","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051587486","display_name":"Z. Jane Wang","orcid":"https://orcid.org/0000-0002-3791-0249"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Z. Jane Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada"],"raw_orcid":"https://orcid.org/0000-0002-3791-0249","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":22.5741,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.99248151,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":"2","first_page":"944","last_page":"950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11325","display_name":"Inertial Sensor and Navigation","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.9022810459136963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7724943161010742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7312291860580444},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6422591805458069},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5406410694122314},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5196862816810608},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44626447558403015},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44180846214294434},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4302586317062378},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3362486958503723},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08718416094779968}],"concepts":[{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.9022810459136963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7724943161010742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7312291860580444},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6422591805458069},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5406410694122314},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5196862816810608},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44626447558403015},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44180846214294434},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4302586317062378},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3362486958503723},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08718416094779968},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2023.3234778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3234778","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","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":26,"referenced_works":["https://openalex.org/W592904438","https://openalex.org/W1964234457","https://openalex.org/W2025768430","https://openalex.org/W2043698790","https://openalex.org/W2094522975","https://openalex.org/W2106171319","https://openalex.org/W2115579991","https://openalex.org/W2124997408","https://openalex.org/W2396274919","https://openalex.org/W2797395780","https://openalex.org/W2896457183","https://openalex.org/W2945763088","https://openalex.org/W2971141820","https://openalex.org/W2998370018","https://openalex.org/W3036812332","https://openalex.org/W3038975720","https://openalex.org/W3091667825","https://openalex.org/W3098486636","https://openalex.org/W3101037136","https://openalex.org/W3122767460","https://openalex.org/W3129245057","https://openalex.org/W3207392858","https://openalex.org/W3211771663","https://openalex.org/W4293363567","https://openalex.org/W4313156423","https://openalex.org/W6726497184"],"related_works":["https://openalex.org/W2091018038","https://openalex.org/W2225378543","https://openalex.org/W9839718","https://openalex.org/W3110613631","https://openalex.org/W4287122200","https://openalex.org/W2742744817","https://openalex.org/W2040913503","https://openalex.org/W3166845860","https://openalex.org/W3202472720","https://openalex.org/W4404994101"],"abstract_inverted_index":{"Inertial":[0],"Measurement":[1],"Unit":[2],"(IMU)":[3],"plays":[4],"an":[5],"important":[6],"role":[7],"in":[8,89],"inertial":[9],"aided":[10],"navigation":[11,35,123],"on":[12,80,126],"robots.":[13],"However,":[14,72],"raw":[15],"IMU":[16,38,119],"data":[17],"could":[18],"be":[19,95,136],"noisy,":[20],"especially":[21],"for":[22,118],"low-cost":[23],"IMUs,":[24],"and":[25,44,53,68,85,115,128],"thus":[26],"requires":[27],"efficient":[28],"pre-processing":[29],"or":[30,97],"denoising":[31,39],"before":[32],"applying":[33],"further":[34],"algorithms.":[36],"Conventional":[37],"approaches":[40],"are":[41,78,131],"mostly":[42],"hand-crafted":[43],"may":[45],"face":[46],"concerns":[47],"such":[48,92],"as":[49],"sensor":[50],"modelling":[51],"errors":[52],"generalization":[54],"issues.":[55],"Several":[56],"recent":[57],"works":[58],"leverage":[59],"deep":[60,75],"neural":[61],"networks":[62],"(DNNs)":[63],"to":[64],"tackle":[65],"this":[66],"problem":[67],"achieve":[69],"promising":[70],"results.":[71],"currently":[73],"reported":[74],"learning":[76,114],"methods":[77,101],"based":[79],"supervised":[81],"learning,":[82],"requiring":[83],"sufficient":[84],"accurate":[86],"annotations.":[87],"While":[88],"real-world":[90],"applications,":[91],"annotations":[93],"can":[94],"expensive":[96],"unavailable,":[98],"making":[99],"these":[100],"not":[102],"practical.":[103],"To":[104],"address":[105],"the":[106],"above":[107],"research":[108],"gap,":[109],"we":[110],"propose":[111],"incorporating":[112],"self-supervised":[113],"future-aware":[116],"inference":[117],"denoising.":[120],"The":[121,133],"end-to-end":[122],"evaluation":[124],"results":[125],"EuRoC":[127],"TUM-VI":[129],"datasets":[130],"promising.":[132],"code":[134],"will":[135],"publicly":[137],"available":[138],"at":[139],"<uri":[140],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[141],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/KleinYuan/IMUDB</uri>":[142],".":[143]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
