Design, Implementation and Key Issues of Adaptive Tightly Coupled MEMS INS/GPS Integration System

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atmire.migration.oldid5378
dc.contributor.advisorEl-Sheimy, Naser
dc.contributor.advisorHai, Zhang
dc.contributor.authorZhou, Qifan
dc.contributor.committeememberEl-Sheimy, Naser
dc.contributor.committeememberLing, Pei
dc.contributor.committeememberHai, Zhang
dc.contributor.committeememberNoureldin, Aboelmagd
dc.contributor.committeememberGao, Yang
dc.contributor.committeememberRui, Zhou
dc.date.accessioned2017-03-02T19:41:43Z
dc.date.available2017-03-02T19:41:43Z
dc.date.issued2017
dc.date.submitted2017en
dc.description.abstractTightly-coupled integrated system is advantageous in providing seamless navigation solution compared with other integration schemes, and is attractive in multiple application fields. This thesis focuses on the design, implementation of adaptive tightly-coupled integrated navigation system with the aiding of external measurement. The key issues investigated and problems solved in this dissertation are: 1. It presents four novel adaptive noise estimation approaches. These methods rely on the observation information to estimate the measurement noise property and error characteristic. The noise assessment method makes use of difference operation to eliminate the effect of other elements and this process is decoupled from the filter calculation loop. Thus, the covariance matrix estimation result will not be coupled with the state vector error, and this existed problem in traditional adaptive Kalman filter is avoided. 2. It proposes a new low-cost MEMS sensor in-filed calibration algorithm. The navigation mission requires calibration before started. The proposed approach can perform calibration of the sensors without any requirement or special needs. The calibration scheme is convenient to be accomplished by simple hand rotation in space. The bias, scale factor error and non-orthogonal error are able to be identified. 3. It investigates the Euler angle based attitude estimation. The Euler angle attitude update is constrained for further practical application owning to its singularity problem. The singularity problem will cause the attitude procedure discontinue and involves more estimation error. An intelligent coordinate switch algorithm is proposed to overcome this drawback and has achieved a good performance. The adaptive noise estimation approach is also applied in the filter to adjust the weight of observation model, which prevents the negative effect of external acceleration. 4. It introduces the adaptive noise estimation theorem and external observation in the standard tightly-coupled integrated system, and establishes the system hardware platform to test the validation. The height and heading information measured by barometer and magnetometer are used involved in measurement model to provide aiding information. A switch filter strategy is designed to save computational time, and the adaptive noise estimation approach is used to acquire the GPS measurement error characteristic. Both simulation and practical tests are conducted to verify the system.en_US
dc.identifier.citationZhou, Q. (2017). Design, Implementation and Key Issues of Adaptive Tightly Coupled MEMS INS/GPS Integration System (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25580en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/25580
dc.identifier.urihttp://hdl.handle.net/11023/3663
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectEngineering
dc.titleDesign, Implementation and Key Issues of Adaptive Tightly Coupled MEMS INS/GPS Integration System
dc.typedoctoral thesis
thesis.degree.disciplineGeomatics Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
ucalgary.item.requestcopytrue
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