{"id":"https://openalex.org/W4407129700","doi":"https://doi.org/10.1109/ieem62345.2024.10857150","title":"Research on Flight Attitude Prediction Method for Multi-rotor UAV Based on CNN-LSTM-attention Model","display_name":"Research on Flight Attitude Prediction Method for Multi-rotor UAV Based on CNN-LSTM-attention Model","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4407129700","doi":"https://doi.org/10.1109/ieem62345.2024.10857150"},"language":"en","primary_location":{"id":"doi:10.1109/ieem62345.2024.10857150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem62345.2024.10857150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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/A5044807661","display_name":"Xuanlu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanlu Chen","raw_affiliation_strings":["Beihang University,School of Reliability and Systems Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Reliability and Systems Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013201771","display_name":"Shenghan Zhou","orcid":"https://orcid.org/0000-0001-7979-4912"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghan Zhou","raw_affiliation_strings":["Beihang University,School of Reliability and Systems Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Reliability and Systems Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102863531","display_name":"Wenbing Chang","orcid":"https://orcid.org/0000-0002-8741-4753"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbing Chang","raw_affiliation_strings":["Beihang University,School of Reliability and Systems Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Reliability and Systems Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020511767","display_name":"Fajie Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fajie Wei","raw_affiliation_strings":["Beihang University,School of Economics and Management,Beijing,China,10019"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,School of Economics and Management,Beijing,China,10019","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045634084","display_name":"Linchao Yang","orcid":"https://orcid.org/0000-0002-9635-2398"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linchao Yang","raw_affiliation_strings":["North China Electric Power University,School of Economics and Management,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North China Electric Power University,School of Economics and Management,Beijing,China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1139","last_page":"1143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11325","display_name":"Inertial Sensor and Navigation","score":0.9771000146865845,"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/T11325","display_name":"Inertial Sensor and Navigation","score":0.9771000146865845,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9387999773025513,"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/T13855","display_name":"Aerospace Engineering and Control Systems","score":0.9021999835968018,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7044270634651184},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5994322299957275},{"id":"https://openalex.org/keywords/rotor","display_name":"Rotor (electric)","score":0.5327648520469666},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44856593012809753},{"id":"https://openalex.org/keywords/attitude-control","display_name":"Attitude control","score":0.4249795973300934},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.23335200548171997},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15572234988212585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7044270634651184},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5994322299957275},{"id":"https://openalex.org/C17281054","wikidata":"https://www.wikidata.org/wiki/Q193466","display_name":"Rotor (electric)","level":2,"score":0.5327648520469666},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44856593012809753},{"id":"https://openalex.org/C155710575","wikidata":"https://www.wikidata.org/wiki/Q83001","display_name":"Attitude control","level":2,"score":0.4249795973300934},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.23335200548171997},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15572234988212585},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem62345.2024.10857150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem62345.2024.10857150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321125","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1650780448","https://openalex.org/W2081474570","https://openalex.org/W3025126338","https://openalex.org/W3163734136","https://openalex.org/W3211167621","https://openalex.org/W4226396475","https://openalex.org/W4294043941","https://openalex.org/W4321636959","https://openalex.org/W4322763686","https://openalex.org/W4366828973","https://openalex.org/W4384026411","https://openalex.org/W4385762365"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,13,108],"unmanned":[4],"aerial":[5,48],"vehicle":[6],"(UAV)":[7],"flight":[8,34,64,81,114,163],"attitude":[9,35],"prediction":[10,103,127],"method":[11,55],"utilizing":[12],"convolutional":[14],"neural":[15],"network":[16,23],"(CNN)":[17],"and":[18,24,51,66,129,144,157],"long":[19],"short-term":[20],"memory":[21],"(LSTM)":[22],"Attention":[25],"mechanism.":[26],"It":[27],"has":[28,148],"become":[29],"particularly":[30],"important":[31],"to":[32,58,68,76,90,101,141],"predict":[33,160],"accurately":[36],"with":[37,107,125],"the":[38,70,92,95,102,118,122,131,137,161],"wide":[39],"application":[40],"of":[41,62,73,94,111],"UAVs":[42],"in":[43,80],"many":[44],"fields":[45],"such":[46],"as,":[47],"photography,":[49],"logistics,":[50],"surveillance.":[52],"The":[53,83],"proposed":[54,119],"uses":[56],"CNN":[57,143],"extract":[59],"spatial":[60],"patterns":[61],"UAV":[63,113,162],"data,":[65],"LSTM":[67,146],"learn":[69],"temporal":[71],"dependencies":[72],"these":[74],"features":[75],"capture":[77],"dynamic":[78],"changes":[79],"attitude.":[82,164],"model":[84,120],"introduces":[85],"attention":[86],"mechanism,":[87],"empowering":[88],"it":[89],"prioritize":[91],"parts":[93],"data":[96],"that":[97,117],"are":[98],"more":[99],"critical":[100],"results.":[104],"Experimental":[105],"results":[106],"certain":[109],"type":[110],"multi-rotor":[112],"parameters":[115],"show":[116],"predicts":[121],"pitch":[123],"angle":[124],"high":[126],"accuracy":[128],"keeps":[130],"error":[132],"low.":[133],"Through":[134],"comparative":[135],"experiments,":[136],"CNN-LSTM-Attention":[138],"Model,":[139],"compared":[140],"simple":[142,145],"models,":[147],"improved":[149],"accuracy,":[150],"slightly":[151],"decreased":[152],"error,":[153],"stronger":[154],"generalization":[155],"ability,":[156],"can":[158],"effectively":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
