Flight maneuver intelligent recognition based on deep variational autoencoder network
The selection and training of aircraft pilots has high standards, long training cycles, high resource consumption, high risk, and high elimination rate. It is the particularly urgent and important requirement for the current talent training strategy of national and military to increase efficiency an...
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| Published in: | EURASIP journal on advances in signal processing Vol. 2022; no. 1; pp. 1 - 23 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Cham
Springer International Publishing
12.03.2022
Springer Springer Nature B.V SpringerOpen |
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| ISSN: | 1687-6180, 1687-6172, 1687-6180 |
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| Abstract | The selection and training of aircraft pilots has high standards, long training cycles, high resource consumption, high risk, and high elimination rate. It is the particularly urgent and important requirement for the current talent training strategy of national and military to increase efficiency and speed up all aspects of pilot training, reduce the training cycle and reduce the elimination rate. To this end, this paper uses deep variational auto-encoder network and adaptive dynamic time warping algorithms as support to explore the establishment of an integrated evaluation system for flight maneuver recognition and quality evaluation, solve the industry difficulty faced by current flight training data mining applications, and achieve accurate recognition and reliable quality evaluation of flight regimes under the background of high mobility. It will fully explore the benefits of existing airborne flight data for military trainee pilots, support the personalized and accurate training of flight talents, and reduce the rate of talent elimination. |
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| AbstractList | The selection and training of aircraft pilots has high standards, long training cycles, high resource consumption, high risk, and high elimination rate. It is the particularly urgent and important requirement for the current talent training strategy of national and military to increase efficiency and speed up all aspects of pilot training, reduce the training cycle and reduce the elimination rate. To this end, this paper uses deep variational auto-encoder network and adaptive dynamic time warping algorithms as support to explore the establishment of an integrated evaluation system for flight maneuver recognition and quality evaluation, solve the industry difficulty faced by current flight training data mining applications, and achieve accurate recognition and reliable quality evaluation of flight regimes under the background of high mobility. It will fully explore the benefits of existing airborne flight data for military trainee pilots, support the personalized and accurate training of flight talents, and reduce the rate of talent elimination. Abstract The selection and training of aircraft pilots has high standards, long training cycles, high resource consumption, high risk, and high elimination rate. It is the particularly urgent and important requirement for the current talent training strategy of national and military to increase efficiency and speed up all aspects of pilot training, reduce the training cycle and reduce the elimination rate. To this end, this paper uses deep variational auto-encoder network and adaptive dynamic time warping algorithms as support to explore the establishment of an integrated evaluation system for flight maneuver recognition and quality evaluation, solve the industry difficulty faced by current flight training data mining applications, and achieve accurate recognition and reliable quality evaluation of flight regimes under the background of high mobility. It will fully explore the benefits of existing airborne flight data for military trainee pilots, support the personalized and accurate training of flight talents, and reduce the rate of talent elimination. |
| ArticleNumber | 21 |
| Audience | Academic |
| Author | Tian, Wei Zhang, Hong Li, Hui Xiong, Yuan |
| Author_xml | – sequence: 1 givenname: Wei orcidid: 0000-0002-2214-5417 surname: Tian fullname: Tian, Wei email: twhztwhz@126.com organization: Jiangxi Hongdu Aviation Industry Group Co. Ltd, Naval Aviation University – sequence: 2 givenname: Hong surname: Zhang fullname: Zhang, Hong organization: Jiangxi Hongdu Aviation Industry Group Co. Ltd – sequence: 3 givenname: Hui surname: Li fullname: Li, Hui organization: Naval Aviation University – sequence: 4 givenname: Yuan surname: Xiong fullname: Xiong, Yuan organization: Jiangxi Hongdu Aviation Industry Group Co. Ltd |
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| Keywords | Variational autoencoder Flight quality evaluation Deep neural network Flight maneuver recognition Dynamic time warping |
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| References | Olemskoi, Kokhan (CR18) 2006; 360 Agrawal, Faloutsos, Swami (CR12) 1993 Xu, Liu (CR25) 2020; 45 Liu, Zhai, Lu, Wu (CR1) 2019; 17 Zhang, Ni (CR6) 2006; S2 Zhou, Fan, Zhang, Huang (CR21) 2017; 18 Xu, Wang, Bai (CR26) 2020; 03 Ni, Shi, Xie, Wang (CR5) 2005 Gao, Ni, Wang, Zhang (CR9) 2011; 18 Pavlidis, Horowitz (CR16) 1974; 23 CR17 Wang, Gao (CR24) 2019; 38 Shen, Ni, Zhang (CR20) 2017; 53 CR14 CR13 Li, Shan, Guo (CR19) 2015; 51 Su, Ni, Wang (CR8) 2011; 47 Liu, Zhang (CR2) 2019; 6 Wang, Gao (CR11) 2018; 38 Yin, Ni (CR7) 2006 Xie, Ni, Zhang, Wang (CR3) 2004; 3 Korn, Jagadish, Faloutsos (CR15) 1997; 26 Xiao, Fu (CR23) 2018; 2 Wang, Gao (CR10) 2018; 33 Xie, Ni, Zhang (CR4) 2005; 12 Shen, Ni, Zhang (CR22) 2019; 20 T Pavlidis (850_CR16) 1974; 23 S Xu (850_CR26) 2020; 03 X Liu (850_CR2) 2019; 6 YC Shen (850_CR20) 2017; 53 YW Wang (850_CR10) 2018; 33 YP Xiao (850_CR23) 2018; 2 850_CR14 850_CR13 C Zhou (850_CR21) 2017; 18 C Su (850_CR8) 2011; 47 RF Zhang (850_CR6) 2006; S2 G Xu (850_CR25) 2020; 45 R Agrawal (850_CR12) 1993 F Korn (850_CR15) 1997; 26 C Xie (850_CR4) 2005; 12 SH Ni (850_CR5) 2005 YW Wang (850_CR11) 2018; 38 WJ Yin (850_CR7) 2006 YW Wang (850_CR24) 2019; 38 A Olemskoi (850_CR18) 2006; 360 850_CR17 Y Gao (850_CR9) 2011; 18 HL Li (850_CR19) 2015; 51 YC Shen (850_CR22) 2019; 20 X Liu (850_CR1) 2019; 17 C Xie (850_CR3) 2004; 3 |
| References_xml | – volume: 20 start-page: 7 issue: 02 year: 2019 end-page: 12 ident: CR22 article-title: Similarity query method for flight data time series sub-sequences publication-title: J. Air Force Eng. Univ. (Natural Science Edition) – volume: 17 start-page: 2052 issue: 3 year: 2019 end-page: 2061 ident: CR1 article-title: QoS-guarantee resource allocation for multibeam satellite industrial internet of things with NOMA publication-title: IEEE Tran. Ind. Inf. doi: 10.1109/TII.2019.2951728 – volume: 6 start-page: 5971 year: 2019 end-page: 5980 ident: CR2 article-title: Rate and energy efficiency improvements for 5G-based IoT with simultaneous transfer publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2018.2863267 – volume: 12 start-page: 169 year: 2005 end-page: 171 ident: CR4 article-title: Pattern attributes extraction of flight data based on rough set publication-title: Comput. Eng. doi: 10.3969/j.issn.1000-3428.2005.12.062 – volume: 03 start-page: 58 year: 2020 end-page: 62 ident: CR26 article-title: Overview of military helicopter training effectiveness based on simulation publication-title: Helicopter Tech. – ident: CR14 – volume: 360 start-page: 37 issue: 1 year: 2006 end-page: 58 ident: CR18 article-title: Effective temperature of self-similar time series: analytical and numerical developments publication-title: Physica A doi: 10.5488/CMP.8.4.761 – volume: 53 start-page: 161 issue: 24 year: 2017 end-page: 167+218 ident: CR20 article-title: Flight action recognition method based on Bayesian network publication-title: Comput. Eng. Appl. doi: 10.3778/j.issn.1002-8331.1707-0156 – volume: 33 start-page: 447 issue: 05 year: 2018 end-page: 451+498 ident: CR10 article-title: A rule extraction method for flight action recognition based on whale optimization algorithm publication-title: J. Naval Aeronaut. Astronaut. Univ. doi: 10.7682/j.issn.1673-1522.2018.05.005 – volume: 45 start-page: 162 issue: 05 year: 2020 end-page: 169 ident: CR25 article-title: An automatic evaluation method for military simulation training result publication-title: Fire Control Command Control doi: 10.3969/j.issn.1002-0640.2020.05.030 – volume: S2 start-page: 109 year: 2006 end-page: 111 ident: CR6 article-title: The algorithm of flight trajectory creatation based on Cardinals cubic splines publication-title: Calc. Technol. Autom. doi: 10.3969/j.issn.1673-4599.2005.01.009 – volume: 47 start-page: 237 issue: 3 year: 2011 end-page: 239 ident: CR8 article-title: Method of rule acquirement of flight state based on improved AIS publication-title: Comput. Eng. Appl. doi: 10.3778/j.issn.1002-8331.2011.03.069 – volume: 2 start-page: 42 issue: 05 year: 2018 end-page: 45 ident: CR23 article-title: A review of the research on lat-eral direction flight quality assessment methods publication-title: J. Civ. Aviat. – volume: 18 start-page: 28 issue: 01 year: 2011 end-page: 31 ident: CR9 article-title: A flight state rule extraction method based on improved quantum genetic algorithm publication-title: Electroopt. Control doi: 10.3969/j.issn.1671-637X.2011.01.007 – volume: 18 start-page: 34 issue: 04 year: 2017 end-page: 39 ident: CR21 article-title: A flight action recognition based on multivariate time series fusion publication-title: J. Air Force Eng. Univ. (Natural Science Edition) doi: 10.3969/j.issn.1009-3516.2017.04.007 – ident: CR17 – volume: 38 start-page: 1 issue: 05 year: 2019 end-page: 4+10 ident: CR24 article-title: Comprehensive evaluation method of UAV flight quality based on comprehensive weighting method publication-title: Ordnance Ind. Autom. doi: 10.7690/bgzdh.2019.05.001 – ident: CR13 – year: 2005 ident: CR5 article-title: Establishment of avion inflight maneuver action recognizing knowledge base publication-title: Comput. Simul. doi: 10.3969/j.issn.1006-9348.2005.04.007 – year: 2006 ident: CR7 article-title: A method of recognizing flight maneuver based on genetic algorithm publication-title: Comput. Dev. Appl. doi: 10.3969/j.issn.1003-5850.2006.04.008 – volume: 51 start-page: 267 issue: 09 year: 2015 end-page: 270 ident: CR19 article-title: Flight action recognition algorithm based on MDTW publication-title: Comput. Eng. Appl. doi: 10.3778/j.issn.1002-8331.1307-0018 – year: 1993 ident: CR12 publication-title: Efficient Similarity Search in Sequence Databases doi: 10.1007/3-540-57301-1_5 – volume: 23 start-page: 860 issue: 8 year: 1974 end-page: 870 ident: CR16 article-title: Segmentation of plane curves publication-title: IEEE Trans. Comput. doi: 10.1109/T-C.1974.224041 – volume: 3 start-page: 240 year: 2004 end-page: 242 ident: CR3 article-title: Recognition method of acrobatic maneuver based on state matching and support vector machines publication-title: J. Project. Rockets Missiles Guidance doi: 10.15892/j.cnki.djzdxb.2004.s3.015 – volume: 38 start-page: 74 issue: 10 year: 2018 end-page: 76 ident: CR11 article-title: Research on complex motion recognition method based on basic flying motion publication-title: Ship Electron. Eng. doi: 10.3969/j.issn.1672-9730.2018.10.018 – volume: 26 start-page: 289 issue: 2 year: 1997 end-page: 300 ident: CR15 article-title: Efficiently supporting ad hoc queries in large datasets of time sequence publication-title: ACM SIGMOD Rec. doi: 10.1145/253262.253332 – volume: 18 start-page: 34 issue: 04 year: 2017 ident: 850_CR21 publication-title: J. Air Force Eng. Univ. (Natural Science Edition) doi: 10.3969/j.issn.1009-3516.2017.04.007 – volume: 53 start-page: 161 issue: 24 year: 2017 ident: 850_CR20 publication-title: Comput. Eng. Appl. doi: 10.3778/j.issn.1002-8331.1707-0156 – year: 2005 ident: 850_CR5 publication-title: Comput. Simul. doi: 10.3969/j.issn.1006-9348.2005.04.007 – volume: 26 start-page: 289 issue: 2 year: 1997 ident: 850_CR15 publication-title: ACM SIGMOD Rec. doi: 10.1145/253262.253332 – volume: 3 start-page: 240 year: 2004 ident: 850_CR3 publication-title: J. Project. Rockets Missiles Guidance doi: 10.15892/j.cnki.djzdxb.2004.s3.015 – volume: 38 start-page: 1 issue: 05 year: 2019 ident: 850_CR24 publication-title: Ordnance Ind. Autom. doi: 10.7690/bgzdh.2019.05.001 – volume: 17 start-page: 2052 issue: 3 year: 2019 ident: 850_CR1 publication-title: IEEE Tran. Ind. Inf. doi: 10.1109/TII.2019.2951728 – volume: S2 start-page: 109 year: 2006 ident: 850_CR6 publication-title: Calc. Technol. Autom. doi: 10.3969/j.issn.1673-4599.2005.01.009 – volume: 33 start-page: 447 issue: 05 year: 2018 ident: 850_CR10 publication-title: J. Naval Aeronaut. Astronaut. Univ. doi: 10.7682/j.issn.1673-1522.2018.05.005 – ident: 850_CR14 doi: 10.1145/1007568.1007636 – volume: 03 start-page: 58 year: 2020 ident: 850_CR26 publication-title: Helicopter Tech. – volume-title: Efficient Similarity Search in Sequence Databases year: 1993 ident: 850_CR12 doi: 10.1007/3-540-57301-1_5 – volume: 20 start-page: 7 issue: 02 year: 2019 ident: 850_CR22 publication-title: J. Air Force Eng. Univ. (Natural Science Edition) – volume: 45 start-page: 162 issue: 05 year: 2020 ident: 850_CR25 publication-title: Fire Control Command Control doi: 10.3969/j.issn.1002-0640.2020.05.030 – volume: 6 start-page: 5971 year: 2019 ident: 850_CR2 publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2018.2863267 – year: 2006 ident: 850_CR7 publication-title: Comput. Dev. Appl. doi: 10.3969/j.issn.1003-5850.2006.04.008 – volume: 23 start-page: 860 issue: 8 year: 1974 ident: 850_CR16 publication-title: IEEE Trans. Comput. doi: 10.1109/T-C.1974.224041 – volume: 18 start-page: 28 issue: 01 year: 2011 ident: 850_CR9 publication-title: Electroopt. Control doi: 10.3969/j.issn.1671-637X.2011.01.007 – ident: 850_CR17 – volume: 2 start-page: 42 issue: 05 year: 2018 ident: 850_CR23 publication-title: J. Civ. Aviat. – volume: 38 start-page: 74 issue: 10 year: 2018 ident: 850_CR11 publication-title: Ship Electron. Eng. doi: 10.3969/j.issn.1672-9730.2018.10.018 – volume: 51 start-page: 267 issue: 09 year: 2015 ident: 850_CR19 publication-title: Comput. Eng. Appl. doi: 10.3778/j.issn.1002-8331.1307-0018 – ident: 850_CR13 – volume: 47 start-page: 237 issue: 3 year: 2011 ident: 850_CR8 publication-title: Comput. Eng. Appl. doi: 10.3778/j.issn.1002-8331.2011.03.069 – volume: 12 start-page: 169 year: 2005 ident: 850_CR4 publication-title: Comput. Eng. doi: 10.3969/j.issn.1000-3428.2005.12.062 – volume: 360 start-page: 37 issue: 1 year: 2006 ident: 850_CR18 publication-title: Physica A doi: 10.5488/CMP.8.4.761 |
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| Snippet | The selection and training of aircraft pilots has high standards, long training cycles, high resource consumption, high risk, and high elimination rate. It is... Abstract The selection and training of aircraft pilots has high standards, long training cycles, high resource consumption, high risk, and high elimination... |
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| SubjectTerms | Aircraft maneuvers Aircraft pilots Algorithms Artificial Intelligence and Cognitive Computing for Smart Internet of Vehicle Coders Consumption (Economics) Data mining Deep neural network Dynamic time warping Engineering Flight maneuver recognition Flight quality evaluation Flight training Pilot training Pilots Pilots and pilotage Quality assessment Quantum Information Technology Recognition Signal,Image and Speech Processing Spintronics Variational autoencoder |
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| Title | Flight maneuver intelligent recognition based on deep variational autoencoder network |
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| Volume | 2022 |
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