Adaptive Dual Wavelet Threshold Denoising Function Combined with Allan Variance for Tuning FOG-SINS Filter
Allan variance (AV) stochastic process identification method for inertial sensors has successfully combined the wavelet transform denoising scheme. However, the latter usually employs a traditional hard threshold or soft threshold that presents some mathematical problems. An adaptive dual threshold...
Saved in:
Published in | Shanghai jiao tong da xue xue bao. Yi xue ban Vol. 25; no. 4; p. 434 |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | Chinese |
Published |
Shanghai
Shanghai Jiaotong University Press
01.08.2020
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Allan variance (AV) stochastic process identification method for inertial sensors has successfully combined the wavelet transform denoising scheme. However, the latter usually employs a traditional hard threshold or soft threshold that presents some mathematical problems. An adaptive dual threshold for discrete wavelet transform (DWT) denoising function overcomes the disadvantages of traditional approaches. Assume that two thresholds for noise and signal and special fuzzy evaluation function for the signal with range between the two thresholds assure continuity and overcome previous difficulties. On the basis of AV, an application for strap-down inertial navigation system (SINS) stochastic model extraction assures more efficient tuning of the augmented 21-state improved exact modeling Kalman filter (IEMKF) states. The experimental results show that the proposed algorithm is superior in denoising performance. Furthermore, the improved filter estimation of navigation solution is better than that of conventional |
---|---|
AbstractList | Allan variance (AV) stochastic process identification method for inertial sensors has successfully combined the wavelet transform denoising scheme. However, the latter usually employs a traditional hard threshold or soft threshold that presents some mathematical problems. An adaptive dual threshold for discrete wavelet transform (DWT) denoising function overcomes the disadvantages of traditional approaches. Assume that two thresholds for noise and signal and special fuzzy evaluation function for the signal with range between the two thresholds assure continuity and overcome previous difficulties. On the basis of AV, an application for strap-down inertial navigation system (SINS) stochastic model extraction assures more efficient tuning of the augmented 21-state improved exact modeling Kalman filter (IEMKF) states. The experimental results show that the proposed algorithm is superior in denoising performance. Furthermore, the improved filter estimation of navigation solution is better than that of conventional |
Author | Bao, Qilian Bessaad, Nassim Sun, Shuodong Du, Yuding Hassan, Mahmood Ul Liu, Lin |
Author_xml | – sequence: 1 givenname: Nassim surname: Bessaad fullname: Bessaad, Nassim – sequence: 2 givenname: Qilian surname: Bao fullname: Bao, Qilian – sequence: 3 givenname: Shuodong surname: Sun fullname: Sun, Shuodong – sequence: 4 givenname: Yuding surname: Du fullname: Du, Yuding – sequence: 5 givenname: Lin surname: Liu fullname: Liu, Lin – sequence: 6 givenname: Mahmood surname: Hassan middlename: Ul fullname: Hassan, Mahmood Ul |
BookMark | eNqNi8sOwUAUQGdB4tV_uIl1kz5QloJiw0LDUqZ66ZVxh3nw-0R8gNVZnHM6osGasSHa8SgbhOM4HrZEYC2VUZSNJmmSRW1xnVby7uiJMPdSwUE-UaGDojZoa60qmCNrssQXyD2fHGmGmb6VxFjBi1wNU6Ukw14aknxCOGsDhefvsF2Gu_VmBzkph6YnmmepLAY_dkU_XxSzVXg3-uHRuuNVe8MfdUwGaRaPJ8MkTf-r3jB8SVk |
ContentType | Journal Article |
Copyright | Copyright Shanghai Jiaotong University Press Aug 2020 |
Copyright_xml | – notice: Copyright Shanghai Jiaotong University Press Aug 2020 |
DBID | 7QL 7QO 7QP 7T5 7TK 7TM 7TO 7U9 8FD C1K FR3 H94 M7N P64 RC3 |
DatabaseName | Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts Calcium & Calcified Tissue Abstracts Immunology Abstracts Neurosciences Abstracts Nucleic Acids Abstracts Oncogenes and Growth Factors Abstracts Virology and AIDS Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database AIDS and Cancer Research Abstracts Algology Mycology and Protozoology Abstracts (Microbiology C) Biotechnology and BioEngineering Abstracts Genetics Abstracts |
DatabaseTitle | Virology and AIDS Abstracts Oncogenes and Growth Factors Abstracts Technology Research Database Nucleic Acids Abstracts Neurosciences Abstracts Biotechnology and BioEngineering Abstracts Environmental Sciences and Pollution Management Genetics Abstracts Biotechnology Research Abstracts Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) AIDS and Cancer Research Abstracts Immunology Abstracts Engineering Research Database Calcium & Calcified Tissue Abstracts |
DatabaseTitleList | Virology and AIDS Abstracts |
DeliveryMethod | fulltext_linktorsrc |
GroupedDBID | -05 7QL 7QO 7QP 7T5 7TK 7TM 7TO 7U9 8FD ALMA_UNASSIGNED_HOLDINGS C1K CCEZO CIEJG FR3 GROUPED_DOAJ H94 M7N P64 RC3 |
ID | FETCH-proquest_journals_24371895233 |
ISSN | 1674-8115 |
IngestDate | Thu Oct 10 22:04:13 EDT 2024 |
IsPeerReviewed | false |
IsScholarly | true |
Issue | 4 |
Language | Chinese |
LinkModel | OpenURL |
MergedId | FETCHMERGED-proquest_journals_24371895233 |
PQID | 2437189523 |
PQPubID | 2048168 |
ParticipantIDs | proquest_journals_2437189523 |
PublicationCentury | 2000 |
PublicationDate | 20200801 |
PublicationDateYYYYMMDD | 2020-08-01 |
PublicationDate_xml | – month: 08 year: 2020 text: 20200801 day: 01 |
PublicationDecade | 2020 |
PublicationPlace | Shanghai |
PublicationPlace_xml | – name: Shanghai |
PublicationTitle | Shanghai jiao tong da xue xue bao. Yi xue ban |
PublicationYear | 2020 |
Publisher | Shanghai Jiaotong University Press |
Publisher_xml | – name: Shanghai Jiaotong University Press |
SSID | ssib007693270 ssib021364667 ssib051367862 ssib006260104 ssib008858007 ssib005076848 ssib006702980 ssib036439378 ssj0001538017 |
Score | 4.519113 |
Snippet | Allan variance (AV) stochastic process identification method for inertial sensors has successfully combined the wavelet transform denoising scheme. However,... |
SourceID | proquest |
SourceType | Aggregation Database |
StartPage | 434 |
SubjectTerms | Algorithms Discrete Wavelet Transform Inertial navigation Inertial sensing devices Kalman filters Mathematical problems Navigation systems Noise reduction Stochastic models Stochastic processes Stochasticity Thresholds Tuning Wavelet transforms |
Title | Adaptive Dual Wavelet Threshold Denoising Function Combined with Allan Variance for Tuning FOG-SINS Filter |
URI | https://www.proquest.com/docview/2437189523 |
Volume | 25 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8NAEF60XryIouKbBb2FiM3m1WOrjVK0RRpfp7IxCU2prWgD0l_vzD6S-EDUQ0JIIGyYL7PffDszS8iRCyFA6ljcjO3ERbUqMnmcMvMksrzUjW2It1HQv-q6Fzd2596pLLSL6pJZdPw4_7au5D9WhXtgV6yS_YNli5fCDbgG-8IZLAznX9m4GfNnmfqDRSB3HDeRmBkhmOcVV5XAmUymmRADApi-hKXh_4dYWOecNwEEE-MW4mVROYAph2EulJKgd272IbI3gmysM3gVh-2jxjzkmTHKOBBX3Kwo5sZbnogj4tNj4yFT1wX0WrjVioRTF_h69lRKqEKsvc7GFaD2cynLDnOImtXcKti2mDHyYr5VcoVVJsspuVIPsQNDFCP8XBFZccauZ5t-XZZ7am8ty6QVKu2K67WVKPqhpXa3NwhuLi8HYfs-XCSLrO7UyFKzddYKSick1iIrTsj6GKO6HnapL50abh5pVZyc7zv-SRlDW3Xm2m7J6RhSPlb2THOwR56vejTKUnYGLEFsAqS_9wsvEGQnXCUrKkqhTQm5NbIwH66TkYYbRbhRBTdawI0WcKMablTDjSLcqIAb1XCjADcq4UY13KiE2wY5DNrh6YWpBzhQ_8PrAFtb1v2GYzG2SWqT6STZIhSmhNiLfJakHrd5jK2B_EbiRI_MSoGsR9tk76c37fz8eJcslxjbI7XZS57sA0mcRQfKzO89zmgy |
link.rule.ids | 315,786,790 |
linkProvider | EBSCOhost |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Adaptive+Dual+Wavelet+Threshold+Denoising+Function+Combined+with+Allan+Variance+for+Tuning+FOG-SINS+Filter&rft.jtitle=Shanghai+jiao+tong+da+xue+xue+bao.+Yi+xue+ban&rft.au=Bessaad%2C+Nassim&rft.au=Bao%2C+Qilian&rft.au=Sun%2C+Shuodong&rft.au=Du%2C+Yuding&rft.date=2020-08-01&rft.pub=Shanghai+Jiaotong+University+Press&rft.issn=1674-8115&rft.volume=25&rft.issue=4&rft.spage=434&rft.externalDBID=NO_FULL_TEXT |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1674-8115&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1674-8115&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1674-8115&client=summon |